1 Chapter 1 RESEARCH DESCRIPTION

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Chapter 1
RESEARCH DESCRIPTION
1.1 Background of the Study
“Primary health services remain elusive or inaccessible to majority of our
population, especially those living in the rural and poor areas of the country…” said
Senator Edgardo J. Angara from the online article entitled “Bring health care to rural areas
using ICT: SOLON” (2011). In another article entitled “Rural Areas suffer most from poor
Health Care System, says Angara” he mentioned about the sufferings experienced by the
Philippines that is the 1:15,000 doctor-to-population ratio which is much worse than in US
who only have a 1:150 (2009). He also added that majority of these doctors reside in urban
areas, thus it will be difficult for people in rural areas to avail their services.
No wonder why most of these people risk their health into self-medication and into
traditional healing better known as herbal medication or even quack doctors. Financial
consideration is another reason why most people in rural areas shift to self-medication
using herbs.
Policarpio “Pol” Cainoy a Doctor of Ministry in Natural Healing (DMNH) and an
expert in alternative healing said that herbal medication is safe; however improper
medication may also cause complications. Same when herbal medicine and synthetic
medicine are used at the same time.
Furthermore, this pushes Senator Angara to promote a national Telehealth system
in the country saying that this means access to quality health care for every Filipino (Rural
Areas suffer most from Poor Health Care System says Angara, 2009). The Telehealth

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includes Information and Communication Technology (ICT). There were developed
systems but these are for-profit and most of these are web-based and computer-based which
requires access to Internet or/and computer.
As of now there are only twenty-five (25) herbalist all over Philippines handling
clinic of herbal & natural healing to be specific that is Dok Alternatibo whom researchers
refer their study. And if that is the case full accommodation to million Filipino patients
seriously implies a problem. (Dok Alternatibo Herbal Medicine Clinic, 2010)
1.2 Statement of the Problem
These are the following problems considered in this study:
a. The delivery of basic health services in remote areas are inadequate. In most
cases, people rely on quack doctors for immediate medical care.
b. While the use herbal medicine is being promoted, people in remote areas are
not familiar with its use and administration. This is aggravated by the lack of
trained herbalist in most areas.
1.3 Research Objectives
The following are the objectives of this research:
1.3.1 General Objective
The objective of this research is to develop an expert system for Android
phones that will be used to diagnose common medical problems and subsequently
prescribe herbal medication for each problem it diagnose.

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1.3.2 Specific Objectives
The specific objectives of the study are the following:
a. To capture the expertise of medical doctors in diagnosing patient’s diseases,
diseases such as gastroenteritis, dysentery, chicken pox, measles, tuberculosis,
sinusitis, cold, pharyngitis, tonsillitis. mumps, typhoid fever, flu, diarrhea,
constipation, hypertension, anemia, dyspepsia, duodenal ulcer, gastric ulcer,
parasitic worms, rheumatism, headache, ,sore throat and abdominal pain;
b. To capture the expertise of an herbalist in prescribing herbal remedies for the
diagnosed diseases covered;
c. To analyze and design rules from the knowledge acquired from the interactive
sessions with the domain experts and other sources such as books and the web.
d. To test and fine tune the encoded knowledge of the expert system.
1.4 Scope and Limitation
The following defines the scope and limitations of the research:
1.4.1 Scope of the Research
a. This expert system models the expertise of a medical doctor in diagnosing an
illness and the expertise of an herbalist in prescribing herbal medicines using
E2GDroid expert system shell.

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1.4.2 Limitations of the Research
a. Only 15 selected approved herbs by Department of Health of the Philippines
were considered and so only those ailments that are within the capabilities of
these herbs were included.
b. Only the following diseases can be diagnosed by the system, gastroenteritis,
dysentery, chicken pox, measles, tuberculosis, sinusitis, cold, pharyngitis,
tonsillitis. mumps, typhoid fever, flu, diarrhea, constipation, hypertension,
anemia, dyspepsia, duodenal ulcer, gastric ulcer, parasitic worms, rheumatism,
headache, ,sore throat and abdominal pain;
c. Chronic diseases of slow progression such as heart disease, stroke, cancer, and
other major diseases are not included in the system.
1.5 Significance of the Research
The developed expert system will serve as a tool for the people in remote areas in
diagnosing the possible disease of the patient and prescribing herbal remedies. The
developed expert system intends to provide alternative approaches to medical care in the
absence of medical health practitioners. This also provides portability since it is mobile-
based and does not require Internet connection; therefore it is usable anytime and
anywhere, addressing scarcity of medical health personnel to deliver medical care.
Moreover, other researchers may use this as their bases in developing reliable application
to support the development of health care in the Philippines.

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CHAPTER 2
REVIEW OF RELATED LITERATURES
This chapter presents past studies and existing systems that researchers used as
basis in the development of the proposed system. The systems keenly differentiated getting
each strengths and weaknesses. Every identified approaches applied are gathered and are
used for the fulfillment of the proposed new approach in relative to the current problem.
Aside from related systems, a brief discussion of the used tool that is through expert system
and an overview of herbal medication are included.
2.1 Related Systems
In this section developed related systems are presented with its characteristics.
2.1.1 MYCIN
It was stated by John Durkin in his book entitled “Expert Systems: Design and
Development” that MYCIN is a rule-based medical expert system, just like the proposed
system. It captures the expertise of a human expert on diagnosing meningitis and
bacteremia infections. It provides consultative advice to the user (physician or doctors)
about the disease. The system has two functions, first is to the blood disease based on the
obtained patient’s medical data and second is to suggest a treatment or prescription. The
system is consist of three sub-systems: consultation system, explanation system and rule
acquisition system. The system considers every single detail and provides acceptable
solutions and conclusions. It also provides accurate and quick diagnosis. However, the
system is only available to meningitis and bacteremia infections. The system is goal-driven
and operates using simple inference engine. It will ask the user a set of yes/no queries then

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provides a conclusion and treatment. The consultation has two phases. First the diagnosis,
wherein most likely infectious organisms are identified. Then, the second phase in the
prescription of one or more drugs that should control for all of the possible organisms
(Durkin, 1994)
The system is an initial step in the development of medical expert systems. It also
serves as a model for the future development of medical expert systems. The system’s
consultation structure serves as a model for the researchers in developing and designing
the proposed expert system.
2.1.2 ONCOCIN: An Expert System for Oncology Protocol
Management
ONCOCIN is a medical expert system. The development of the consultation system
addresses questions regarding the optimal representation of complex medical knowledge.
Its function is to assist physicians in the treatment of cancer patients. The system is a rule
based system that uses forward chaining. ONCOCIN allows an interaction with historical
data but it requires inference rules based on assessment trends. The domain knowledge is
represented using four main types of data structure: Contexts, Parameters, Rules, and
Control Blocks. Contexts represent concepts or entities of the domain about which the
system needs static knowledge, and aid in organizing the knowledge base. Contexts may
be a disease, protocol or chemotherapy. Parameters represent the attributes of patients,
drugs, tests, etc. A rule concludes a value for some parameter on the basis of values of
other parameters. Control blocks contains an ordered set of steps to be used for
accomplishing a specific task. (E.H. Shortliffe,2013)

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The project seeks to identify new techniques for bringing large AI programs to a
clinical audience. The system also needs for improved data collection and decision making.
Just like the proposed system, the system also tends to develop a system that can
aid in medical health care.
2.1.3 Herbal Prescriber Database
According to Christopher Hobbs the developer of Herbal Prescriber Database, this
system is an online database of herbs, ailments, and the corresponding uses. It provides
herbal prescriptions for a certain disease. It gives an option to the user whether to explore
through selecting or searching an herb or ailment. Each herb includes a brief information,
dosage and ailments treated. Each ailment on the other hand includes its description along
with its treatment plan. Furthermore, it provides a list of recommended herbal remedies
(Christopher Hobbs’ Herbal Prescriber Database, 2012).
The interface is made simple with herbs and ailments in table form. First letters of
every word are provided. Also, a search bar for direct query for a specific herb or ailment
is provided.
A constant dosage for all ailments associated to a specified herbal plant is included;
however the instruction on how to use is not clearly presented. Because of this, a
misunderstanding between the application and the user might happen; leading to improper
medication and may result to complications.
The system is relevant to the proposed system since it also prescribe herbal
remedies to health problems. This provides the researchers an insight on how to present the
herbal prescription in the proposed system.

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Figure 2.1. Herbal Prescriber Database Home Page
2.1.4 Herbs
Herbs is a commercialized, computer-based software created by Zentrum
Publishing. According to the developer, this software has eight panels; Herbal Listing,
Image Browser, Herbal Actions, Commission E, Digestive System, Text Files, Data Bank
and Resources. As stated, Herbal Listing is a section of the system that contains the brief
information, dosage and description of the inputted herbal plant. On the other hand, Image
browser lets the user browse stored images of herbal plants. While, Herbal Actions gives a
list of curable health concerns by a specific herbal plant. Furthermore, Commission E
where affliction corresponds to some possible medical herbal remedies determined
according to herbal actions that are approved by German Commission E.
The system allows user to search by inputting the name of a specific herbal plant
and the software gives the list of herbal medication it is capable of. However, the system
does not clearly present what specific affliction can it treat.

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The succeeding figures showcase the screen shots of Herbs software interface.
Figure 2.2 shows herbal software home page the starting page of the software where eight
panels are listed. Figure 2.3 is the Commision E page that presents the list of afflictions
and its corresponding medicinal herbal remedies and at the same page Figure 2.4 the Herbal
Listing page consist of herbal plant and its information which includes its botanical and
other names, parts used, dosage, actions, description and references for further reading.
Just like the proposed system, this system deals with herbal remedy prescription.
Its prescription are based on the active properties of each herbs that will address the disease.
Unlike the proposed system, this is not an expert system. In addition, the proposed system
used only those proven herbal plants, which used to cure diseases for a long time.
Figure 2.2. Herbal Software Home Page

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Figure 2.3. Commission E Page
Figure 2.4. Herbal Listing Page

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2.1.5 FAPDA: First Aid Pharmaceutical Digital Assistant
Oladosu and Adedeji stated on their paper that First Aid Pharmaceutical Digital
Assistant is a first aid drug prescription software deployed for small mobile devices. The
mobile patient can consult with the expert system anywhere. The communication between
the patient and the expert system is interactive. The expert system sends the diagnosis
decision to the electronic-Prescription warehouse at the end of the consultation. The
electronic-Prescription system then sends an electronic- Prescription to the pharmacy from
where drug can be delivered to the patient or collected by the patient. The mobile
application resides on the mobile terminal using both its memory and processing power.
Mobile service infrastructure is responsible for providing the General Packet Radio Service
(GPRS), 3G or any related connectivity technology, which the mobile terminal uses in
transferring data. The server is responsible for Authentication and authorization, Context
extraction, Message switching and transfer. The pharmacy database is used for keeping the
names of prescribed drugs from the electronic-prescription system and sending the
prescription to the parcel delivery service for home delivery to the patient or alternatively
kept with the pharmacy for patient to pick up. This pharmacy database comprised the
names of prescribed drugs from the virtual doctor for the treatment of four common
ailments namely: malaria, pneumonia, conjunctivitis, and gastroenteritis. The service
registry is responsible for keeping the database and monitoring it. Moreover, it provides a
number of other services to the upper layers (Adedeji & Oladosu, 2011).
Figure 2.5 on page 11 conceptualized FAPDAas it was describe from the preceding
paragraph.

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Figure 2.5. The Scope Model of FAPDA
The proposed system adapted the way FAPDA cater the system to the users and that
is through mobile phones that is widely available nowadays.
2.2 An Expert System
An expert system is an interactive computer-based decision tool that uses both facts
and heuristics to solve difficult decision problems based on knowledge acquired from an
expert. It may be viewed as a computer simulation of a human expert. The most
fundamental different between expert system and conventional computer program is that
"expert systems manipulate knowledge while conventional programs manipulate data.

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2.2.1 Advantages of an Expert System
Between the Expert System and human expertise, there are some pro and cons.
There are several advantages in using Expert System compare to the problem solving using
the human (Adedeji Bodunde Badiru, 2012):
1. Human expertise is very scarce.
2. Humans get tired from physical or mental workload.
3. Humans forget crucial details of a problem.
4. Humans are inconsistent in their day-to-day decisions.
5. Humans have limited working memory.
6. Humans are unable to comprehend large amounts of data quickly.
7. Humans are unable to retain large amounts of data in memory.
8. Humans are slow in recalling information stored in memory.
9. Humans are subject to deliberate or inadvertent bias in their actions.
10. Humans can deliberately avoid decision responsibilities.
11. Humans lie, hide, and die.
2.2.2 Review on Expert System Shells
Below are different expert system shells reviewed to determined the best shell for
the development of the system. These include: ESTA, Jess, Esys Corvid and e2gDroid.
E2gDroid is discussed in details in the theoritical framework of this book.

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2.2.2.1 Expert System Shell for Text Animation (ESTA)
As stated from the journal entry submitted by Prasad, et al. entitled “Using ESTA
to develop Expert System for the Natural Resource Management”, ESTA is an expert
system shell developed by PDC (Prolog Development Center), Denmark, which is written
in visual prolog. It is an executable, ready-to-run expert system shell application that is
easy and manageable, which provides numerous features to the developers. It was designed
with facilities for an easy editing of the knowledge-base. It also has two knowledge
representation, and these are Section and Parameter. Section contains the representation of
rules of the knowledge base in “IF-THEN” format. It is where defined parameters are used
inside rules. On the other hand, Parameter defines the variable that holds specific values
from either input form the user or from inferred by the system. This parameter also includes
the question of the sytem to the user, the explanation why such question is asked, and the
picture that best described the question for better interpretation of the question asked. It is
capable of giving conclusion using either forward or backward chaining. Moreover, it has
additional built-in procedure like sound, which generates an audio through the computers
loudspeaker lasting the given duration and with the given frequency. Also this shell is able
to call other applications may it either be DOS or Windows application through its built-in
procedure called system. This shell also supports the use of mathematical functions in cases
calculation is necessary (Prasad, et al., 2003).
2.2.2.2 Java Expert System Shell (Jess)
Jess is a rules-engine for java platform developed by Ernest Friedman-Hill at
Sandia National Laboratories in Livermore, CA. It was considered as the first rule engine
that supports JSR94 industry-standard rule engine API. It can either run as a standalone

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program or usually embed the Jess library in Java code and manipulate it using its own
Java API. Thus, making it popular in building java software that has the capacity to
“reason” using knowledge supplemented in the form of declarative rules. What makes this
kind of expert system shell amazing is that it is small, light and one of the fastest rule
engines developed. In addition to that, it uses declarative paradigm instead of procedural
paradigm which means this continuously applies a collection of rules to a collection of
facts by the process of pattern matching supported by Rete algorithm which is an efficient
pattern matching algorithm for implementing production rule system. Moreover, this
expert system shell supports either forward or backward chaining in providing conslusions.
It has its own declarative XML rule language called JessML, which is designed to be easy
to transform into other XML rule language as well as into the Jess rule language
(www.jessrules.com).
2.2.2.3 Exsys Corvid
Exsys Corvid, developed by the Exsys Inc. in 1983, is a knowledge automation
expert system software capable of handling acquired knowledge in order to build powerful
interactive advisory applications to be delivered online, as stated from its wedsite. It
supports easy, cross-platform Java-Based Web Deployment. Aside from catering expert
system online, it could also be used as stand-alone system. For its knowledge base, it uses
and made enhanced traditional rule-based approach wit an “object structure” use of
variables supporting methods and properties. Thus, provides many of the benefits of object-
oriented programming. Thus, this shell accordingly, is a very flexible and powerful
development environment that can be quickly and easily learned. Moreover, rules are
defined, organized and structured into logically related blocks with the use of Logic Blocks.

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Logic Blocks are made up of one or more tree-structured diagrams. These are very versatile
and can be run via forward or backward chaining (www. exsys.com).
2.2.2.4 Summary of the Reviewed Shells
All mentioned shells has its own features like flexibility, ease of use, learnability,
some provide API to support improving the interface or the entire system through
imbedding it to other supported platforms, some also provides built-in procedures to
improve results, and some support online delivery of the system. It could also be observed
that all of the shells represents knowledge using rule-based system. However, these shells
are developed for PC applications only and are not intended to support mobile phones.
Hence, the researchers of this study use e2gDroid Lite to deploy expert system inside
mobile phones. This shell also share some of the features with the other mentioned shells.
Like representing rules using rule-based system, the use of links that allows to attach
pictures and delivering the knowledge base either online or via micro SD cards. Further
discussion about e2gDroid is found at chapter 3 Theoritical Framework under subsection
entitled “The Shell”.
2.3 Herbal Medication
For how many years herbal plants became the ultimate partner of human in curing
diseases. Every herb is unique and each has its own way in treating ailments. Some are
used through detraction, some are taken as a tea, and some are used as lotion etc.
An herb is defined as food that contains medicinal qualities that is use to normalize
and ensure balance within the body system. Unlike synthetic drugs, herbs support the
immune system's defense mechanism in treating diseases. Synthetic drugs do not provide

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mechanism in normalizing the system because it is weakened by the added chemicals
(Using Herbal Medicines Safely – A Practical Guide, 2010). More often these chemicals if
tolerated without the right prescription could kill. Nowadays these synthetic drugs are
moderated and several drug companies are now shifting in the use of pure herbs.
In contrast to the above statements researchers state that there are still dangers in
taking herbs, however it has less side effects than commercialized drugs. There are also
herbs that are bad for the lactating or/and pregnant mothers for they are strong enough for
the babies. Some herbs may have acute side effects like rashes or may be asthma and other
allergy reaction. Taking herbs and commercialized drugs at the same time has a dangerous
effect on a human's body. These drugs alternate the pure substance within the herb by the
injected chemicals in it, converting the herb as a harmful element to the system. Like for
instance the aspirin or warfarin known to prevent clotting of blood inside the arteries reduce
stroke and heart disease, however if it is taken with chamomile, garlic, ginger, aloe vera,
ginko or ginseng the effect is reverse, it increases the bleeding.(Wong, 2008)
Thus proper prescription should be followed with according to what Ferrell, et. al.
(2004) believed.

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Chapter 3
THEORETICAL FRAMEWORK
This chapter discusses Artificial Intelligence (AI) theories, AI formalisms and
related topics that were engaged in the development of an expert system.
3.1 A Rule-based Expert System
Rule-based system is simple, consisting of little more than a set of if-then
statements, but provide the basis for so-called "expert systems" which are widely used in
many fields. The concept of an expert system is this: the knowledge of an expert is encoded
into the rule set. When exposed to the same data, the expert system Al will perform in a
similar manner to the expert.
To create a rule-based system for a given problem, you must have (or create) the
following (James Freeman-Hargis, 2001):
1. A set of facts to represent the initial working memory. This should be anything
relevant to the beginning state of the system,
2. A set of rules. This should encompass any and all actions that should be taken
within the scope of a problem, but nothing irrelevant. The number of rules
in the system can affect its performance, so you don't want any that aren't
needed.
3. A condition that determines that a solution has been found or that none exists.
This is necessary to terminate some rule-based systems that find themselves
in infinite loops otherwise
Flow chart is created for visual representation of how the system works. Figure 3.1
illustrates the process flow of the expert system.

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Figure 3.1 The Conceptual Model of an Expert System
3.2 Knowledge Engineering
The process whereby knowledge from an expert or group of experts or other sources
such as books, procedure manuals, training guides, etc. are gathered, formatted, verified
and validated, and inputted into the knowledge base of the expert system is called
Knowledge Engineering .A knowledge engineer is someone involved in the whole process
of knowledge engineering by investigating a particular domain, determining what concepts
are important in that domain, and creating a formal representation of the objects and
relations in the domain (Russell & Norvig, 1995). The domain expert will be the knowledge
engineer’s source knowledge by which the knowledge engineer makes his set of inference
rules. Knowledge engineering has two important sub-processes aside from other processes,
namely knowledge acquisition and knowledge base Design.

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3.2.1 Knowledge Acquisition
This is the process wherein the knowledge engineer extracts, structures and
organizes knowledge from the domain. The knowledge engineer being the one involved in
knowledge acquisition must understand enough about the domain so that he can be able to
represent this knowledge into important objects and relationships (Russell & Norvig,
1995).
3.2.2 Knowledge Base Design
Designing the knowledge base of the expert system is the second stage of
knowledge acquisition. The design of the knowledge base is the translation of the domain-
level concepts to logic-level names (Russell & Norvig, 1995). The knowledge base will
contain the specialized knowledge in the form of rule based representation. The knowledge
base will serve as the primary building block of the expert system (Alivio, et al.). Being
the one involved in the design of the expert system’s knowledge-base, the knowledge
engineer must understand enough about the representation language to correctly encode
the knowledge.
3.3 Knowledge Base
The knowledge base will contain the specialized knowledge in the form of rule
based representation. The knowledge base will serve as the primary building block of the
expert system. A knowledge base is created by knowledge engineers, who translate the
knowledge of the human experts into rules. The design of the knowledge base is the
translation of the domain-level concepts to logic-level names (Russell & Norvig, 1995).

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It is part of the shell where rules as the knowledge is collected by inference engine
to satisfy facts and then to generate conclusions.
3.4 The Inference Engine
The inference engine is the control mechanism that organizes the problem data and
searches through the knowledge base for applicable rules. It applies the axiomatic
knowledge in the knowledge base to the task-specific data to arrive at some solution or
conclusion (Russell & Norvig, 1995).
3.4.1 Forward Chaining
Forward chaining is one of the two main methods of reasoning when using
inference rule. It can be describe through repeated application of Modus Ponens. This is
use by the rule base moving directions of the antecedents to the consequent of the rule
(Vermesan, 1999). Its implementation begins with initial information that goes on
generating more and more information until it achieves the final decision.
3.4.2 Backward Chaining
Backward chaining begins with the original problem statement. It is used to
backtrack from a goal to the paths that lead to the goal. A goal is specified and the expert
system tries to determine what conditions are needed to arrive at the specified goal (Russell
& Norvig, 1995).
3.5 Production Rules
Production rule, which makes up production system or production rule system, was
defined as the intellectual precursor best describe the rule-based expert system architecture

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(Luger and Stubblefield, 1998). It is composed of two parts a sensory precondition or “IF
statement” and an action or “THEN”.
3.5.1 Propositional Logic
Propositional logic involves logical connectives such as "or" and "and",
determining the truth-values of the propositions. Propositional logic is concerned with
propositions and their relationships.
There are two types of sentences in propositional logic, the simple sentences and
the compound sentences. Simple sentences are atomic expressions. Compound sentences
express logical relationships between simple sentences. It is composed of two or more
simple statements known as components. Also, components may be compound statements.
Connectives or also known as logical operators joins simple sentences into compound
sentences, and joins compounds into larger compounds.
Table 3.1 Propositional Logic Symbols
Symbol Definition
A Assertion
~A Negation
A B Conjunction
A B Disjunction
A⇒ B Implication
A⇐ B Reduction
A⇔ B equivalence

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3.6 Resolution Principle
In determining the truth of an assertion of logical systems, inference strategy is
used. The resolution principle is a theorem proving method by constructing refutation
proofs. In proof by resolution, unification is used. This method attempts to prove negation
of the goal –P cannot be TRUE. New resolvents are produced from the union of existing
axioms and the negated theorem.
Example:
KB = [ A -> B, A, ¬B]
KB = [ ¬A˅B, A, ¬B]
Premises: 1. A -> B
2. A
Goal: B
obtaining,
¬A˅B A
B ¬B
3.7 The Shell
An expert system shell is a tool used in developing expert systems. It is a tool that
provides rule-based programming suitable for automating an expert system. The use of it
aids developers in building the system because it is already defined as an expert system
whose knowledge base is left empty, ready to accept new knowledge from the developers.
This also provides hustle-free implementation since the developers only concentrate on
entering knowledge base without building anything (Eldrandaly, 2007).

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Figure 3.2 Expert system structure
3.7.1 E2gdroid Lite
The e2gDroid lite or e2gDroid for short is an e2gLite version designed to deliver
an expert system through Android phones. As default to expert system shells, it has the
capability of reasoning through the supplemented knowledge that could be loaded either
from online storage like servers, phone’s internal memory or from external memories like
micro SDs. For its knowledge base, it uses production rules that is in “If … Then” format
that it reads rules sequentially and generate conclusions using the backward chaining
technique.
Another feature of this shell is on the simplicity of its knowledge base. The syntax
is so simple that it is similar on writing rules in English version, no complicated syntax to
be familiar with. This knowledge base is then saved in an external .kb file located on a
folder named e2kb which is created by the shell during its installation. In addition to that,
the file is constant that the same file is loaded both in e2gLite for web applications and for
phone using e2gDroid.

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Chapter 4
Methodology
This chapter discusses the essential steps needed in developing an expert system.
4.1 Knowledge Engineering
“Knowledge Engineering is the process of developing knowledge based systems in
any field, whether it be in the public or private sector, in commerce or in industry”
(Debenham, 1989). It refers to any activities that demand acquisition and representation of
knowledge (Oxford, 1989-1990). In this phase, the knowledge engineers are the proponents
of the system.
The following are the knowledge engineering activities that the developers
conducted:
Phase 1: Problem Assessment
Phase 2: Knowledge Acquisition
Phase 3: System Design
Phase 4: Testing and Evaluation
Phase 5: Documentation
Phase 6: Maintenance
Though the activities are shown in sequence, the process is highly iterative. There
is also overlapping in the execution of each activities.

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Figure 4.1 Knowledge engineering

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4.1.1 Problem Assessment Phase
This is the phase of the research where the researchers should identify and justify
the problem. This is the phase where the assessment of the feasibility and applicability of
an expert system solution to a problem should be done. The scope and limitations of the
research is also identified during this phase.
4.1.2 Knowledge Acquisition Phase
In this phase knowledge acquisition from the domain expert and/or other resources
such as books and other reading materials are involved. It also involves the documentation,
interpretation and analysis of the acquired knowledge. Knowledge acquisition itself is a
cycle. It begins with collection of knowledge, then interpretation and analysis. Then, a
method is designed to clarify the collected knowledge and collection of knowledge is done
again for additional knowledge for the knowledge base. The collection of knowledge will
be done through interviews; structured and non-structured, questionnaires, observations
and self-elicitation.
4.1.3 Design Phase
This phase is where the acquired knowledge is represented in selected
representation such as first order predicate knowledge, and frames and slots. The elicited
rules represented in specific knowledge representation scheme is also encoded into
computer readable format. Rules will be test for its correctness which is done through
resolution method; wherein at the end a contradiction must be presented. The researchers
may use the aid of decision graphs and trees in coding the rules in the system. Subsequent
to this is the interface design of the system.

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4.1.4 Testing Phase
This is the phase wherein a demonstration of the system prototype to the users and
the expert is done. Once the expert system prototype has been approved by the expert, the
proponents continued the development effort by fine-tuning the knowledge representation.
In case there are errors, necessary changes shall be made.
4.1.5 Documentation Phase
After the development of the expert system, a documented report is to be produced.
A documentation is needed to ensure that the system is working as it is supposed to be, and
for quick debugging, recovery from errors. Therefore, it is better to have a documentation.
The documented report should contain the system development and the other aspects
involved. It should contain all the necessary information about the project. The document
must also contain explanations on how to operate the system and source codes to serve as
a reference for future researchers.
4.1.6 Maintenance Phase
After testing the system, maintenance is needed. Depending on the user’ needs, the
knowledge base will be updated form time to time.

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Chapter 5
Results and Discussions
This chapter discusses the steps done in the developing the expert system
application and the results in each phases,
5.1 Assessment Phase
In this phase the problem was identified. Furthermore, scope and limitations of the
study were also clearly defined. Resources such as books, electronic materials, internet
articles and other sources which the researchers considered in the fulfillment of this
research were all known. In addition, human experts, an herbalist and a medical doctor,
were also identified. A rule engine was considered and studied for the experimentation in
the implementation of the prescription process.
This expert system addressed a well-defined problem. In this phase the researchers
needed considered candidate problems that have chances for success. While health care is
primarily inaccessible to majority of the population in the Philippines, it has been decided
the study will be focused on health care problems. Due to inaccessible health care, and
financial aspect issues, most of the people from rural areas are shifting into traditional
medication and self-medication using herbs. Expert on this field are small in number. In
the current situation, consulting a medical doctor or even an herbalist requires time and
effort and also money on the patient's side. To sum up all, these are the tasks done by the
researchers in this phase:
1. Determined the motivation of the project.
2. Identified and justified the project description.

30
3. Determined the resources for extraction of knowledge.
4. Write the proposal
5.2 Knowledge Acquisition Phase
Expert system is a software that simulates the knowledge of an expert in specific
subject and its expertise thus the knowledge in the knowledge base relies directly from the
knowledge given by the experts. In this phase, series of interview were conducted to
capture the knowledge of the experts regarding on herbal prescription and disease
diagnosis. Domain experts include an herbalist in the person of Doc. Policarpio Cainoy
DMNH and a medical doctor, Dr. Muhammad M. Putting, M.D. of MSU-IIT clinic
department. They are the source of knowledge that were acquired and were encoded into
rules in the knowledge base. Dr. Cainoy’s expertise in prescribing herbal medication was
accumulated to form the prescription phase of the system while Dr. Putting’s expertise in
diagnosing diseases was used to construct the diagnosing phase. The researchers made
appointments with the domain experts, based on agreed schedules. The sessions with the
domain experts were interactive. The researchers also used other methods in obtaining the
required knowledge such as researching and referring from books and verified it with the
domain experts.
The overall system’s knowledge is composed of two phases; the diagnosis and
the prescription phase, which requires two different experts from two different fields of
expertise. The medical doctor from MSU-IIT clinic in person of Dr. Muhammad M. Puting
assessed in molding the knowledge by confirming the information that the knowledge
engineers had gathered about the covered diseases. He also shared his experiences on
diagnosing different cases of diseases and the techniques on how to do it. The basic and

31
widely used on identifying different diseases is through the presented signs and symptoms.
The researchers also observed the normal procedure during consultation sessions that
happened inside the clinic. First, the nurse checks the patient’s body temperature if there
is an inflammation happened. Then, further signs and symptoms are listed down. This
information is pass to Dr. Puting for final analysis and medical prescription.
The system’s final phase is prescription using herbal medication or natural
healing. The same techniques of acquiring knowledge were applied. In this phase, Doc.
Policarpio “Pol” Cainoy who is one of the twenty-five (25) herbalists all over the
Philippines maintaining the only Herbal Center in Iligan City located at 2nd Floor,Valera
Bldg., Roxas Avenue,Mahayahay, Iligan City is the domain expert. The knowledge
engineers presented the selected diseases to Doc. Pol and asked for possible medications
for each, the procedure that must be done most specifically on how to prescribe such
medication considering additional necessary information like age, gender and cases like
pregnancy and the things to avoid.
All necessary data were gathered and were carefully organize to ensure validity and
safety of the result. Other supporting articles like experts’ written knowledge were also
reviewed since every expert has its own interpretations towards the problem. Necessary
factors and patterns were also verified in support to the validity of the system.
In one of the interviews conducted with Dr. Putting, he mentioned that the
temperature is checked first in diagnosing the patient’s disease. Next to that is to check the
physical manifestations or symptoms that is present to the patient. So, in this system, the
developers followed this order.

32
The second phase of the system is the prescription phase. In this phase, Dr.
Policarpio Cainoy, a Doctor of Ministry in Natural Healing and an expert in alternative
healing is the domain expert. Series of interviews were conducted with the domain expert.
Books were also used for further readings and verifications. Dr. Cainoy explained
thoroughly the healing abilities of herbs. He provided the necessary data needed in
developing the prescribing phase. In prescribing herbal medications, several things should
also be considered. The age of the patient is very important in prescribing since the dosage
of the medication is based on the patient’s age. Cases of pregnancy also needs to be
considered.
5.2.1 Acquired Knowledge
After acquiring knowledge from domain experts, knowledge engineers came up
with a grouping of facts necessary to generate conclusions. Below is the grouping of facts,
used in constructing rules for the knowledge base.
GASTROENTERITIS
 Fever: frequent, loose, watery stools: body malaise: sunken eyeball:
abdominal pain: obstruction: bloated, full and tight feeling of the abdomen:
frequent discharge of intestinal gas or fart
OR
 Fever: infrequent, difficulty in having bowel movement: abdominal pain:
sensation of incomplete: bowel evacuation: obstruction: bloated, full and tight
feeling of the abdomen: frequent discharge of intestinal gas or fart

33
DYSENTERY
abdominal pain: obstruction: tenesmus: blood on the stool
OR
sensation of incomplete: bowel evacuation: obstruction: tenesmus: blood on the
stool
CHICKEN POX
 Fever: itchy skin rashes: developed pruritic papules: headache: developed
round pimples filled with fluid and appear like water blisters
MEASLES
 Fever: itchy skin rashes: eyes turn into red and become sensitive to light: have
nasal discharges accompanied by often sneezing and watery eyes: cough
SINUSITIS
 Fever: cough: headache: have nasal discharges accompanied by often sneezing
and watery eyes: feel pain on the face: dizziness
COLD
 Fever: cough: headache:have nasal discharges accompanied by often sneezing
and watery eyes: sore throat

34
TUBERCULOSIS
 Fever: cough: sputum has blood: shortness of breath: chest pain
PHARYNGITIS
 Fever: headache: sore throat: swallowing difficulty or chewing: swollen lymph
nodes
TONSILLITIS
nodes: swelling tonsils
OR
nodes: swelling tonsils: tonsils: secrets coronet
OR
nodes: swelling tonsils: tonsils were surrounded by white patches or pus
[suppurative]
OR
nodes: swelling tonsils: tonsils secrets coronet: tonsils were surrounded by
white patches or pus [suppurative]

35
MUMPS
nodes: swelling of one or both salivary glands: feel pain around the affected
area
TYPHOID FEVER
abdominal pain: obstruction: itchy skin rashes: headache: sore throat
OR
sensation of incomplete: bowel evacuation: obstruction: itchy skin rashes:
headache: sore throat
FLU
abdominal pain: obstruction: cough: headache: nasal discharges accompanied
by often sneezing and watery eyes: sore throat: difficulty in swallowing or
chewing: swollen lymph nodes
OR
sensation of incomplete: bowel evacuation: obstruction: cough: headache:
nasal discharges accompanied by often sneezing and watery eyes: sore throat:
difficulty in swallowing or chewing: swollen lymph nodes

36
RHEUMATISM
 Joint pain: affected joints have crepitus sound: muscle stiffness
SORE THROAT
 Sore throat
DIARRHEA
 Abdominal pain: frequent, loose, watery stools: body malaise: sunken eyeballs
ABDOMINAL PAIN
 Abdominal pain
CONSTIPATION
 Abdominal pain: infrequent, difficulty in having bowel movement: sensation of
incomplete bowel evacuation
DYSPEPSIA
 Abdominal pain: bloated, full and tight feeling of the abdomen:
Gastroesophageal Reflux Disease: burning sensation of the stomach:
grumbling and growling of the stomach: often belching
HEADACHE
 Headache

37
ANEMIA
 Pale skin, nails, lips and eyes: gums often bleeds: have long duration of
bleeding and it takes long time for clothing: alopecia: sensitiveness to cold
HYPERTENSION
 Headache: body malaise: shortness of breath: dizziness: heart palpitation: pain
in the nape: sweating: anxiety: unconsciousness
GASTRIC ULCER
 Abdominal pain: bloated, full and tight feeling of the stomach: headache:
Gastroesophageal Reflux Disease: burning sensation in your stomach:
grumbling and growling of the stomach: often belching: abdominal pain
AFTER taking the meal and taking meal increases the pain
DUODENAL ULCER
 Abdominal pain: bloated, full and tight feeling of the stomach: headache:
Gastroesophageal Reflux Disease: burning sensation in your stomach:
grumbling and growling of the stomach: often belching: abdominal pain
BEFORE taking the meal and taking aspirin or drinking orange or coffee
increases the pain
PARASITIC WORMS
 Abdominal pain: frequent, loose, watery stools: bloated, full and tight feeling
of your abdomen: pale skin, nails, lips and eyes: often bleeding of the gums:
long duration of bleeding and it takes long time for clotting: alopecia:

38
sensitiveness to cold: body malaise: sunken eyeballs: gluttony: appearance of
worms in the stools
OR
 Abdominal pain: infrequent, difficulty in having bowel movement: bloated, full and
tight feeling of your abdomen: pale skin, nails, lips and eyes: often bleeding of the
gums: long duration of bleeding and it takes long time for clotting: alopecia:
sensitiveness to cold: sensation of incomplete bowel evacuation: gluttony:
appearance of worms in the stools
5.3 Design Phase
The construction of the knowledge base happened in this phase. The knowledge
acquired were transformed into rules which can be encoded and stored in the knowledge
base that can be access using Android phones. To store the rules, an expert system shell is
necessary. A good expert system shell has the fundamental feature of an expert system that
has a knowledge base separated from its control and inference engine. For this project, an
expert system shell called as e2gDroid Lite was used. The knowledge base of this shell is
located inside a folder created during the installation of this shell. The knowledge base is
a .kb file. Furthermore, the overall structure of the system would be Expert System =
e2gDroid Lite + Knowledge base (.kb file).
Figure 5.1 presents the overall design of the system which include designing the
rules to be supplemented into the shell and the e2gDroid Lite –the shell itself.

39
Figure 5.1 the overall Design of the system.
There are two phases in this expert system. First is the diagnosing phase and second
is the prescription phase. The knowledge in the diagnosing phase was primarily provided
by the domain expert which is the medical doctor. As to this study, the domain expert is
Dr. Muhammad Putting.
In this study, the system is a rule-based expert system. Thus, the knowledge base
contains the rules which are the elicited knowledge.
In designing the knowledge for the knowledge base, the acquired knowledge from
domain experts was transformed into set of rules. Rules that follows the format of a
production rule system that is in an “If…Then” format. The “If” part or the premise should
logically relate to the information in the “Then” part or the conclusion. These designed
rules were encoded in the .kb file, which is then stored in a folder named e2gkb created by
the shell, where the shell locates its knowledge base. The control or working memory holds

40
the facts inferred by the system provided by the user or during the session. This facts or
information supports the overall operation of the system. These are also used in firing
appropriate rules to generate reliable conclusions or recommendations. In e2gDroid the
facts that are being supplemented or inferred are assigned to different variables, which acts
as an index that points to the corresponding facts making the matching for rules much
faster. In addition, e2gDroid also used backward chaining as its inference method for
reasoning that starts with goals to draw conclusions.
5.3.1. Rule Design
After analyzing the acquired knowledge, rules were then constructed. The
constructed rules are shown below.
RULE [#1]
IF patient’s temperature is > 40
THEN "Patient is prone to convulsion. Patient's possible disease is not part of the domain."
RULE [#2]
IF patient’s temperature is > 37.5 and <= 40
THEN patient has fever
RULE [#3]
IF patient has temperature <= 37.5 and >= 34
THEN patient don’t have fever
RULE [#4]
IF patient has temperature < 40 and >=34
AND patient has frequent, loose, watery stools

41
AND patient has body weakness
AND patient has sunken eyeball
AND patient has abdominal pain
THEN patient has diarrhea symptoms
RULE [#5]
AND patient has infrequent, difficulty in having bowel movement
AND patient has incomplete bowel evacuation
THEN patient has constipation symptoms
RULE [#6.1]
IF patient has diarrhea symptoms
THEN patient has bowel movement problem
RULE [#6.2]
IF patient has constipation symptoms
RULE [#7]
IF patient has fever
AND patient has bowel movement problem
THEN patient has abdominal infection
RULE [#8]

42
AND patient has itchy skin rashes
THEN patient has skin infection
RULE [#9]
AND patient has headache
THEN patient has head infection
RULE [#10]
IF patient has nasal discharges accompanied by often sneezing and watery eyes
THEN patient has runny nose
RULE [#11]
AND patient has runny nose
AND patient has cough
THEN patient has blocked airway
RULE [#12]
AND patient has strep throat
AND patient has swallowing difficulty or chewing
THEN patient has throat infection
RULE [#13]
IF patient has head infection

43
THEN patient has mouth problem
RULE [#14]
IF patient has abdominal infection
AND patient has obstruction
THEN patient has serious abdominal infection
RULE [#15]
IF patient has blocked airway
AND patient has mouth problem
THEN patient has cold symptoms
RULE [#16]
IF patient has mouth problem
AND patient has throat infection
AND patient has swollen lymph nodes
THEN patient has pharyngitis symptoms
RULE [#17]
IF patient has serious abdominal infection
AND patient has patient has bloated, full and tight feeling of his abdomen
AND patient has frequent discharge of intestinal gas or fart
THEN patient has GASTROENTERITIS
RULE [#18]
AND patient has tenesmus

44
THEN patient has DYSENTERY
RULE [#19]
IF patient has skin infection
AND patient has developed pruritic papules on my skin
AND patient has head infection
AND patient has developed has round pimples filled with fluid and appear like water
blisters
THEN patient has CHICKEN POX
RULE [#20]
IF patient has skin infection
AND patient’s eyes turn into red and become sensitive to light
AND patient has blocked airway
THEN patient has MEASLES
RULE [#21]
AND patient has cough
AND patient has blood in sputum
AND patient has shortness of breathing
AND patient has chest pain
THEN patient has TUBERCULOSIS
RULE [#22]
IF patient has head infection
AND patient has blocked airway
AND patient has facial pain

45
AND patient experience dizziness
THEN patient has SINUSITIS
RULE [#23]
IF patient has cold symptoms
THEN patient has COLD
RULE [#24]
IF patient has pharyngitis symptoms
THEN patient has PHARYNGITIS
RULE [#25.1]
AND patient has swelling tonsils
THEN patient has TONSILLITIS
RULE [#25.2]
AND patient’s tonsil/s secret/s coronet
RULE [#25.3]
AND patient’s tonsil/s was surrounded by white patches or pus [suppurative]

46
RULE [#26]
AND patient has swelling of one or both salivary glands
AND patient has pain on affected area
THEN patient has MUMPS
RULE [#27]
AND patient has skin infection
AND patient has mouth problem
THEN patient has TYPHOID FEVER
RULE [#28]
AND patient has pharyngitis symptoms
AND patient has cold symptoms
THEN patient has FLU
RULE [#29]
IF patient don’t have fever
THEN patient has SORE THROAT
RULE [#30]
AND patient has Gastroesophageal Reflux Disease

47
THEN patient has heartburn
RULE [#31]
THEN patient has internal gas problem
RULE [#32]
AND patient has headache
THEN patient has head problem
RULE [#33]
AND patient’s stool type is normal
THEN patient has ABDOMINAL PAIN
RULE [#34]
IF patient has head problem
THEN patient has HEADACHE
RULE [#35]
IF patient has head problem
AND patient has shortness of breathing
AND patient experience dizziness

48
AND patient experience heart palpitation
THEN patient has heart problem
RULE [#36]
AND patient has pale skin, nails, lips and eyes
AND patient has often gum bleeding
AND patient have long duration of bleeding and it takes long time for clotting
AND patient alopecia (hair loss)
AND patient becomes sensitiveness to cold
THEN patient has anemia symptoms
RULE [#37]
IF patient has internal gas problem
AND patient has heartburn
AND patient has burning sensation in your stomach
AND patient has stomach grumbling and growling
AND patient often experience belching
THEN patient has dyspepsia symptoms
RULE [#38]
IF patient has dyspepsia symptoms
AND patient has head problem
THEN patient has peptic ulcer symptoms
RULE [#39]

49
AND patient has joint pain
AND patient has crepitus sound on his joints
AND patient has muscle stiffness
THEN patient has RHEUMATISM
RULE [#40]
AND patient has constipation symptoms
THEN patient has CONSTIPATION
RULE [#41]
AND patient has diarrhea symptoms
THEN patient has DIARRHEA
RULE [#42]
IF patient has heart problem
AND patient has pain in the nape
AND patient is often sweating
AND patient is anxiety
AND patient is unconscious
THEN patient has HYPERTENSION
RULE [#43]
IF patient has anemia symptoms
THEN patient has ANEMIA

50
RULE [#44]
IF patient has bowel movement problem
AND patient has internal gas problem
AND patient has anemia symptoms
AND patient is always hungry although he has eaten lots of food
AND patient notice some appearance of worms in your stools
THEN patient has PARASITIC WORMS
RULE [#45]
IF patient has dyspepsia symptoms
THEN patient has DYSPEPSIA
RULE [#46]
IF patient has peptic ulcer symptoms
AND patient has abdominal pain BEFORE taking my meal and taking aspirin or drinking
orange or coffee increases the pain
THEN patient has DUODENAL ULCER
RULE [#47]
IF patient has peptic ulcer symptoms
AND patient has abdominal pain AFTER taking my meal and taking meal increases the
pain
THEN patient has GASTRIC ULCER

51
Rules for prescribing herbal remedies:
RULE [#49 GASTROENTERITIS]
IF patient has GASTROENTERITIS
THEN suggested treatment is Lemon Grass Decoction
RULE [#50 PARASITIC WORMS]
IF patient has PARASITIC WORMS
AND patient is not pregnant
THEN suggested treatment is Ringworm Bush Decoction
RULE [#51 DYSENTERY]
IF patient has DYSENTERY
THEN suggested treatment is Avocado Decoction
AND suggested treatment is Coconut Decoction
AND suggested treatment is Star Apple Decoction
RULE [#52 DYSENTERY]
IF patient has DYSENTERY
THEN suggested treatment is Pineapple Fruit

52
RULE [#53 TUBERCULOSIS]
IF patient has TUBERCULOSIS
THEN suggested treatment is Onion Eaten Raw
RULE [#54 TUBERCULOSIS]
IF patient has TUBERCULOSIS
AND patient don’t have hypotension
THEN suggested treatment is Garlic Juice
RULE [#55 COLD]
IF patient has COLD
THEN suggested treatment is Snake Weed Decoction
AND suggested treatment is Lemon Grass Decoction
AND suggested treatment is Lemon Grass Steam Bath
AND suggested treatment is Ginger Steam Inhalation
AND suggested treatment is Five-leaf Chaste Tree Decoction
RULE [#56 PHARYNGITIS]
IF patient has PHARYNGITIS
THEN suggested treatment is Snake Weed Gargle

53
RULE [#57 TONSILLITIS]
IF patient has TONSILLITIS
AND suggested treatment is Papaya Fruit Poultice
AND suggested treatment is Chilli Fruit infusion
RULE [#58 TONSILLITIS]
IF patient has TONSILLITIS
THEN suggested treatment is Garlic Raw Candy
RULE [#59 MUMPS]
IF patient has MUMPS
AND suggested treatment is Sensitive Plant Paste
AND suggested treatment is Bilimbi Tree Poultice"
RULE [#60 TYPHOID FEVER]
IF patient has TYPHOID FEVER

54
AND suggested treatment is Onion Eaten Raw"
RULE [#61 FLU]
IF patient has FLU
RULE [#62 SORE THROAT]
IF patient has SORE THROAT
THEN suggested treatment is Garlic Raw Candy
AND suggested treatment is Garlic Juice
RULE [#63 SORE THROAT]
IF patient has SORE THROAT
THEN suggested treatment is Chilli Leaves Gargle
AND suggested treatment is Chilli Plaster

55
AND suggested treatment is Coconut Infusion
AND suggested treatment is Country Borage Heated
AND suggested treatment is Snake Weed Gargle
AND suggested treatment is Ginger Decoction
RULE [#64 ABDOMINAL PAIN]
IF patient has ABDOMINAL PAIN
THEN suggested treatment is Chilli Fruit Infusion
AND suggested treatment is Chilli Fruit Tea
AND suggested treatment is Country Borage Juice
AND suggested treatment is Papaya Fruit with Seeds
RULE [#65 HEADACHE]
IF patient has HEADACHE
THEN suggested treatment is Country Borage Pounded Fresh Leaves
AND suggested treatment is Avocado Decoction Hot Compress
AND suggested treatment is Lemon Grass Liniment
AND suggested treatment is Star Fruit Poultice
AND suggested treatment is Sambong Poultice
AND suggested treatment is Five-leaf Chaste Tree Pounded

56
RULE [#66 RHEUMATISM]
IF patient has RHEUMATISM
THEN suggested treatment is Onion Eaten Raw
AND suggested treatment is Chilli Plaster
AND suggested treatment is Lemon Grass Liniment
AND suggested treatment is Guava Pounded
AND suggested treatment is Ginger Pounded
RULE [#67 CONSTIPATION]
IF patient has CONSTIPATION
AND suggested treatment is Jack Fruit
AND suggested treatment is Onion Eaten Raw
AND suggested treatment is Papaya Fruit
AND suggested treatment is Sensitive Plant Leaves Infusion
AND suggested treatment is Sweet Basil Leaves or Roots Decoction

57
RULE [#68 CONSTIPATION]
IF patient has CONSTIPATION
THEN suggested treatment is Papaya Raw Fruit
RULE [#69 DIARRHEA]
IF patient has DIARRHEA
AND suggested treatment is Jack Fruit Tea
AND suggested treatment is Sweet Basil Leaves or Roots Decoction
AND suggested treatment is Guava Bark Decoction
AND suggested treatment is Guava Leaves Decoction
AND suggested treatment is Ginger Juice
AND suggested treatment is Star Apple Decoction
RULE [#70 HYPERTENSION]
IF patient has HYPERTENSION
THEN suggested treatment is Lemon Grass Decoction
RULE [#71 HYPERTENSION]

58
IF patient has HYPERTENSION
THEN suggested treatment is Garlic Eaten Raw
RULE [#72 ANEMIA]
IF patient has ANEMIA
THEN suggested treatment is Sponge Gourd
THEN suggested treatment is Papaya Seeds
AND suggested treatment is Sponge Gourd Seed Infusion
THEN suggested treatment is Ringworm Bush Seeds

59
THEN suggested treatment is Garlic Decoction
RULE [#76 DYSPEPSIA]
IF patient has DYSPEPSIA
THEN suggested treatment is Papaya Fruit with Seeds
AND suggested treatment is Papaya Fruit
RULE [#77 DYSPEPSIA]
IF patient has DYSPEPSIA
THEN suggested treatment is Papaya Raw Fruit
AND suggested treatment is Pineapple Fruit
RULE [#78 DUODENAL ULCER]
IF patient has DUODENAL ULCER
THEN suggested treatment is Onion with Honey
AND suggested treatment is Jack Fruit Latex
AND suggested treatment is Papaya Leaves Juice
AND suggested treatment is Country Borage Juice for External

60
RULE [#79 DUODENAL ULCER]
IF patient has DUODENAL ULCER
THEN suggested treatment is Papaya Latex
AND suggested treatment is Papaya Raw Fruit
RULE [#80 GASTRIC ULCER]
IF patient has GASTRIC ULCER
THEN suggested treatment is Papaya Latex
AND suggested treatment is Papaya Raw Fruit
RULE [#81 CHICKEN POX]
IF patient has CHICKEN POX
THEN suggested treatment is Star Fruit Poultice
AND suggested treatment is Cassava Starch Bath

61
RULE [#82 MEASLES]
IF patient has MEASLES
THEN suggested treatment is Star Fruit Poultice
AND suggested treatment is Cassava Starch Bath
AND suggested treatment is Mangosteen Rind Decoction"
RULE [#83 SINUSITIS]
IF patient has SINUSITIS
THEN suggested treatment is Mayana Heated
AND suggested treatment is Sambong Heated
Decision Graphs
Figure 5.2. Decision Graph for diseases with fever as dominated symptom.

62
SYMBOLS
A. patient’s temperature is > 40
B. "Patient is prone to convulsion. Patient's
possible disease is not part of the
domain."
C. patient notice some appearance of
worms in your stools
D. patient has temperature < 40 and > 34.1
E. patient has abdominal pain BEFORE
taking my meal and taking aspirin or
drinking orange or coffee increases the
pain
F. patient’s temperature is > 37.5 and < 40
G. patient has fever
H. patient’s temperature < 37.6 and > 34.1
I. patient don’t have fever
J. patient has Frequent, loose, watery
stools
K. patient has body weakness
L. patient has sunken eyeball
M. patient has abdominal pain
N. patient has diarrhea symptoms
O. patient has Infrequent, difficulty in
having bowel movement
P. patient has incomplete bowel
evacuation
Q. patient has obstruction
R. patient has constipation symptoms
S. patient has bowel movement problem
T. patient has abdominal infection
U. patient has itchy skin rashes
V. patient has skin infection
W. patient has headache
X. patient has head infection
Y. patient has nasal discharges
accompanied by often sneezing and
watery eyes
Z. patient has runny nose
AA. patient has cough
BB. patient has blocked airway
CC. patient has strep throat
DD. patient has swallowing difficulty or
chewing
EE. patient has throat infection
FF. patient has mouth problem
GG. patient has serious abdominal infection
HH. patient has swollen lymph nodes
II. patient has patient has bloated, full and
tight feeling of his abdomen
JJ. patient has frequent discharge of
intestinal gas or fart
KK. patient has abdominal pain AFTER
taking my meal and taking meal
increases the pain
LL. patient has tenesmus
MM. patient is always hungry although he
has eaten lots of food
NN. patient has developed pruritic papules
on my skin
OO. patient has developed has round
pimples filled with fluid and appear like
water blisters
PP. patient’s eyes turn into red and become
sensitive to light
QQ. patient has blood in sputum
RR. patient has shortness of breathing
SS. patient has chest pain
TT. patient has facial pain
UU. patient experience dizziness
VV. patient has cold symptoms
WW. patient has swelling tonsils
XX. patient’s tonsil/s secret/s
YY. patient has pharyngitis symptoms
ZZ. patient has swelling of one or both
salivary glands
AAA. patient has pain on affected area
BBB. patient has Gastroesophageal Reflux
Disease
CCC. patient has heartburn
DDD. patient has internal gas problem
EEE. patient has head problem
FFF. patient experience heart palpitation
GGG. patient has heart problem
HHH. patient has pale skin, nails, lips and eyes
III. patient has often gum bleeding
JJJ. patient have long duration of bleeding
and it takes long time for clotting
KKK. patient alopecia (hair loss)
LLL. patient becomes sensitiveness to cold
MMM. patient has anemia symptoms
NNN. patient has burning sensation in your
stomach
OOO. patient has stomach grumbling and
growling
PPP. patient often experience belching
QQQ. patient has dyspepsia symptoms
RRR. patient is unconscious
SSS. patient has peptic ulcer symptoms
TTT. patient has joint pain
UUU. patient has crepitus sound on his joints
VVV. patient has muscle stiffness
WWW. patient has pain in the nape
XXX. patient is often sweating
YYY. patient is anxiety
ZZZ. patient’s tonsil/s was surrounded by

63
Figure 5.3. Decision Graph for other diseases which symptoms does not include fever.
SYMBOLS
A. patient’s temperature is > 40
B. "Patient is prone to convulsion. Patient's
possible disease is not part of the
domain."
C. patient notice some appearance of
worms in your stools
D. patient has temperature < 40 and > 34.1
E. patient has abdominal pain BEFORE
taking my meal and taking aspirin or
drinking orange or coffee increases the
pain
F. patient’s temperature is > 37.5 and < 40
G. patient has fever
H. patient’s temperature < 37.6 and > 34.1
I. patient don’t have fever
J. patient has Frequent, loose, watery
stools
K. patient has body weakness
L. patient has sunken eyeball
M. patient has abdominal pain
N. patient has diarrhea symptoms
O. patient has Infrequent, difficulty in
having bowel movement
P. patient has incomplete bowel
evacuation
Q. patient has obstruction
R. patient has constipation symptoms
S. patient has bowel movement problem
T. patient has abdominal infection
U. patient has itchy skin rashes
V. patient has skin infection
W. patient has headache
X. patient has head infection
Y. patient has nasal discharges
accompanied by often sneezing and
watery eyes
Z. patient has runny nose
AA. patient has cough
BB. patient has blocked airway
CC. patient has strep throat
DD. patient has swallowing difficulty or
chewing
EE. patient has throat infection
FF. patient has mouth problem
GG. patient has serious abdominal infection
HH. patient has swollen lymph nodes
II. patient has patient has bloated, full and
tight feeling of his abdomen
JJ. patient has frequent discharge of
KK. patient has abdominal pain AFTER
taking my meal and taking meal
increases the pain
LL. patient has tenesmus
MM. patient is always hungry although he
has eaten lots of food
NN. patient has developed pruritic papules
on my skin
OO. patient has developed has round
pimples filled with fluid and appear like
water blisters

64
PP. patient’s eyes turn into red and become
sensitive to light
QQ. patient has blood in sputum
RR. patient has shortness of breathing
SS. patient has chest pain
TT. patient has facial pain
UU. patient experience dizziness
VV. patient has cold symptoms
WW. patient has swelling tonsils
XX. patient’s tonsil/s secret/s
YY. patient has pharyngitis symptoms
ZZ. patient has swelling of one or both
salivary glands
AAA. patient has pain on affected area
BBB. patient has Gastroesophageal Reflux
Disease
CCC. patient has heartburn
DDD. patient has internal gas problem
EEE. patient has head problem
FFF. patient experience heart palpitation
GGG. patient has heart problem
HHH. patient has pale skin, nails, lips and eyes
III. patient has often gum bleeding
JJJ. patient have long duration of bleeding
and it takes long time for clotting
KKK. patient alopecia (hair loss)
LLL. patient becomes sensitiveness to cold
MMM. patient has anemia symptoms
NNN. patient has burning sensation in your
stomach
OOO. patient has stomach grumbling and
growling
PPP. patient often experience belching
QQQ. patient has dyspepsia symptoms
RRR. patient is unconscious
SSS. patient has peptic ulcer symptoms
TTT. patient has joint pain
UUU. patient has crepitus sound on his joints
VVV. patient has muscle stiffness
WWW. patient has pain in the nape
XXX. patient is often sweating
YYY. patient is anxiety
ZZZ. patient’s tonsil/s was surrounded by
5.3.2. User Interface Design
User interface is one of the major components of an expert system. It serves as the
channel for the user and the system to interact. The data acquired during the session will
be used to drive the system in firing rules. E2gDroid was used by the researchers due to its
capability of handling interactivity between the system and the user. Like other expert
system shells, only the knowledge base is empty and everything are all defined in e2gDroid
including interactive buttons, check boxes, and text fields. In here, questions are in the form
of “prompt” definition. According to eXpertise2Go.com, this prompt defines format of user
request for an attribute’s value if the inference engine allow it to request. Questions to ask
user is on the next line in single or double quotes below the keyword PROMPT, which
user’s response is then assign to a specific variable for rule matching. Figure 5.4 is a sample
interface of the system’s interface with its actual code on its right.

65
Figure 5.4. Prompt Code
One of the features of e2gDroid is the capability of the knowledge base to
optionally link to Web pages for help (“Infolinks”) or to support conclusions
(“Hyperlinks”). In addition, these links may refer to files locally located on phone’s internal
or external memory. The researchers, to help user about the question and for more detailed
conclusion use this technique. Figure 5.5 – 5.8 are screenshots of the systems
implementation of the technique.
Figure 5.5 Prompted question with Infolink.

66
Figure 5.5 shows the interface of the prompt where the user is asked to input the
value of a parameter. There are four buttons included in the panel . The Submit button
confirms the input of the user. The Why button links to the e2gDroid explanation
subsystem. The Go Back button allows the user to the value of the inputted paramaters.
And lastly, the Exit button allows the user to terminate the application. The “?” button
allows the user to display additional information about the question. Shown in figure 5.6
is the page that shows the additional information about the question.
Figure 5.6. Infolink Page Figure 5.7. Conclusion
Shown in figure 5.7 is the window that displays the final result or conclusion of the system.

67
Figure 5.8. Procedure and dosage of the prescribed herbal treatment.
A web page that presents the image, procedure and dosage of the prescribed herbal
treatment. This appear after user select one of the suggested treatment at figure 5.8.
5.4 Testing Phase
This is the phase wherein a demonstration of the system prototype to the users and
the expert is done. Once the expert system prototype has been approved by the expert, the
proponents continued the development effort by fine-tuning the knowledge representation.
After the system’s overall structure has been defined and the prototype has been
constructed, the designed rules must be tested. In this phase, the researchers manually
tracked every fired rules. Moreover, for documentation purposes Typhoid Fever was used
in later part to illustrate the process of testing.
In order to run the system “Herbal Prescriber on Android.kb” was loaded to the
e2gDroid shell by choosing the knowledge base from the drop-down list menu. The
consultation starts by getting the signs and symptoms observed by the patient. This was
simulated from the traditional and basic consultation that happens inside the clinic. The

68
researchers named this phase as the “Diagnose Phase”, which is used to identify the root
illness experienced by the patient. In addition, all symptoms are first identified either there
is an elevation of the body temperature; this is also used to shorten the procedure. After
this phase, a list of herbal treatments are presented, the number of suggested herbal
treatment is filtered base on the cons of the suggested herb, for instance garlic is not for
patient having hypertension and pineapple is not good for pregnant women. This phase was
named as the “Prescription phase”.
Below is the presentation of the testing procedure of the system assuming that the
patient has a typhoid fever. This is to show how the rules behave. In addition, screenshots
of the actual implementation of the system inside Android phone is included.
5.4.1 Test for the Correctness of Rules (Resolution Principle)
In this part, the correctness of each of the designed rules was tested through
resolution principle.
To show the correctness of rules using resolution principle, the rules that were
included or needed for the “Gastroenteritis” disease were taken as an example.
The Rules
RULE [#17]
AND patient has frequent discharge of intestinal gas or fart
THEN patient has GASTROENTERITIS

69
RULE [#14]
AND patient has obstruction
THEN patient has serious abdominal infection
RULE [#7]
AND patient has bowel movement problem
THEN patient has abdominal infection
RULE [#2]
IF 37.6<= patient’s temperature < 40
THEN patient has fever
RULE [#6.1]
RULE [#6.2]
IF patient has constipation symptoms

70
RULE [#4]
IF patient has temperature < 40 and > 34.1
RULE [#5]
IF patient has temperature < 40 and > 34.1
AND patient has infrequent, difficulty in having bowel movement
AND patient has incomplete bowel evacuation
THEN patient has constipation symptoms
The rules above are in English form, represented by phrases and words in
diagnosing Gastroenteritis. Each rule is referred to as a proposition. A proposition is a
statement consisting of subject and predicate that is either true or false. In expert systems,
the Boolean truth value is asserted into the working memory.

71
Rules were represented by symbolic variables. In showing this rules were
represented by a set of conditions such as S = {S1…. Sn}. The disease were represented as
D = { D1… Dn} which is the goal.
Conditions:
S1 patient has serious abdominal infection
S2 patient has patient has bloated, full and tight feeling of his abdomen
S3 patient has frequent discharge of intestinal gas or fart
S4 patient has abdominal infection
S5 patient has obstruction
S6 patient has fever
S7 patient has bowel movement problem
S8 37.6<= patient’s temperature < 40
S9 patient has diarrhea symptoms
S10 patient has constipation symptoms
S11 patient has temperature < 40 and > 34.1
S12 patient has frequent, loose, watery stools
S13 patient has body weakness
S14 patient has sunken eyeball
S15 patient has abdominal pain
S16 patient has infrequent, difficulty in having bowel movement
S17 patient has incomplete bowel evacuation
D1 GASTROENTERITIS
Rules were then represented in symbolic forms.
Rule 2 S8 ⇒ S6
Rule 4 S11 S12 S13 S14 S15 ⇒ C9

72
Rule 5 S4 S5 ⇒ S1
Rule 6.1 S9 ⇒ S7
Rule 6.2 S10 ⇒ S7
Rule 7 S6 S7 ⇒ S4
Rule 17 S1 S2 S3⇒ D1
After the representation of the rules into symbolic forms, the resolution principle
was done through the following steps:
A. Rules were transformed into clause form:
Rule2 ~ S8 S6
Rule 4 ~S11 ~ S12 ~ S13 ~ S14 ~ S15 C9
Rule 5 ~ S4 ~ S5 S1
Rule 6.1 ~ S9 S7
Rule 6.2 ~ S10 S7
Rule 7 ~ S6 ~ S7 S4
Rule 17 ~ S1 ~ S2 ~ S3 D1
B. Axioms were shown in clause form:
1. ~ S8 S6
2. ~S11 ~ S12 ~ S13 ~ S14 ~ S15 S9
3. ~ S4 ~ S5 S1
4. ~ S9 S7
5. ~ S10 S7
6. ~ S6 ~ S7 S4
7. ~ S1 ~ S2 ~ S3 D1
8. S5
9. S8
10. S10
11. S11
12. S12
13. S13
14. S14

73
15. S15
16. S2
17. S3
18. ~ D1
To prove that D1 is the logical consequence of the given premises, resolution
principle was used. This method assumes that the goal is false and the premises are true
and show that a contradiction exists. With that, the negation of the goal was added to the
set of clauses. New resolvents are produced by pairing clauses with complimentary literals.
At the end of the process, when a contradiction exists or is established, then it shows that
the argument is valid. The resolution tree which presents the whole resolution process in
showed in Figure 5.9
Paired Clauses:
1. Clauses 2 and 4, resulting to
~S11 ~ S12 ~ S13 ~ S14 ~ S15 S7
2. The resulting axiom was then paired to clauses 5 and 6, resulting to
~S11 ~ S12 ~ S13 ~ S14 ~ S15 ~ S6 S4 ~ S10
3. The resulting axiom was then paired to clause 1 , resulting to
~S11 ~ S12 ~ S13 ~ S14 ~ S15 S4 ~ S10 ~ S8
~S11 ~ S12 ~ S13 ~ S14 ~ S15 ~ S10 ~ S8 ~ S5 S1
~S11 ~ S12 ~ S13 ~ S14 ~ S15 ~ S10 ~ S8 ~ S5 ~ S2 ~ S3 D1
~S11 ~ S12 ~ S13 ~ S14 ~ S15 ~ S10 ~ S8 ~ S2 ~ S3 D1
~S11 ~ S12 ~ S13 ~ S14 ~ S15 ~ S10 ~ S2 ~ S3 D1
~S11 ~ S12 ~ S13 ~ S14 ~ S15 ~ S2 ~ S3 D1
~ S12 ~ S13 ~ S14 ~ S15 ~ S2 ~ S3 D1
~ S13 ~ S14 ~ S15 ~ S2 ~ S3 D1
~ S14 ~ S15 ~ S2 ~ S3 D1
~ S15 ~ S2 ~ S3 D1

74
~ S2 ~ S3 D1
~ S3 D1
D1
16. The resulting axiom was then paired to clause 18 , resulting to a contradiction
which is
D1 ~ D1
∴ the argument is valid.
The Resolution Tree
Figure 5.9 Resolution Tree for Diagnosing Gastroentiritis

75
Test for correctness of rules in diagnosing parasitic worms.
The rules
RULE [#3]
IF patient has temperature <= 37.5 and >= 34
THEN patient don’t have fever
RULE [#4]
RULE [#6.1]
RULE [#31]
THEN patient has internal gas problem
RULE [#36]
AND patient has pale skin, nails, lips and eyes
AND patient has often gum bleeding
AND patient have long duration of bleeding and it takes long time for clotting

76
AND patient alopecia (hair loss)
AND patient becomes sensitiveness to cold
THEN patient has anemia symptoms
RULE [#44]
IF patient has bowel movement problem
AND patient has internal gas problem
AND patient has anemia symptoms
AND patient is always hungry although he has eaten lots of food
AND patient notice some appearance of worms in your stools
THEN patient has PARASITIC WORMS
Conditions:
S1 patient’s temperature < = 37.5o
C and >= 34o
C
S2 patient don’t have fever
S3 patient has frequent, loose, watery stools
S4 patient has body weakness
S5 patient has sunken eyeball
S6 patient has abdominal pain
S7 patient has diarrhea symptoms
S8 patient has patient has bowel movement problem
S9 patient has patient has bloated, full and tight feeling of his abdomen
S10 patient has internal gas problem
S11 patient has pale skin, nails, lips and eyes
S12 patient has often gum bleeding
S13 patient have long duration of bleeding and it takes long time for clotting
S14 patient alopecia (hair loss)
S15 patient becomes sensitiveness to cold

77
S16 patient has anemia symptoms
S17 patient is always hungry although he has eaten lots of food
S18 patient notice some appearance of worms in your stools
S19 patient has temperature < 40 and >=34
D patient has PARASITIC WORMS
Rules in symbolic forms:
Rule 3 S1 ⇒ S2
Rule 4 S19 S3 S4 S5 S6 ⇒ S7
Rule 6.1 S7 ⇒ S8
Rule 31 S2 S9 ⇒ S10
Rule 36 S2 S11 S12 S13 S14 S15 ⇒ S16
Rule 44 S8 S10 S16 S17 S18 ⇒ D
A. Rules were transformed into clause form:
1. Rule 3 ~S1 S2
2. Rule 4 ~S19 ~S3 ~S4 ~S5 ~S6 S7
3. Rule 6.1 ~S7 S8
4. Rule 31 ~S2 ~S9 S10
5. Rule 36 ~S2 ~S11 ~S12 ~S13 ~S14 ~S15 S16
6. Rule 44 ~S8 ~S10 ~S16 ~S17 ~S18 D
B. Axioms were shown in clause form:
1. ~S1 S2
2. ~S19 ~S3 ~S4 ~S5 ~S6 S7
3. ~S7 S8
4. ~S2 ~S9 S10
5. ~S2 ~S11 ~S12 ~S13 ~S14 ~S15 S16
6. ~S8 ~S10 ~S16 ~S17 ~S18 D
7. S1
8. S3
9. S4
10. S5

78
11. S6 12. S9
13. S11
14. S12
15. S13
16. S14
17. S15
18. S17
19. S18
20. S19
21. ~D
Below are paired clauses, that results to a new resolvent.
Paired Clauses:
1. Clauses 6 and 3, resulting to
~S10 ~S16 ~S17 ~S18 D ~S7
2. The resulting axiom was then paired to clause 4, resulting to
~S16 ~S17 ~S18 D ~S7 ~S2 ~S9
~S17 ~S18 D ~S7 ~S2 ~S9 ~S2 ~S11 ~S12 ~S13 ~S14 ~S15, notice that if P P ≡ P
by idempotency law for . ∴ the above resolvent becomes
~S17 ~S18 D ~S7 ~S2 ~S9 ~S11 ~S12 ~S13 ~S14 ~S15
~S17 ~S18 D ~S7 ~S9 ~S11 ~S12 ~S13 ~S14 ~S15 ~S1
~S17 ~S18 D ~S9 ~S11 ~S12 ~S13 ~S14 ~S15 ~S1 ~S19 ~S3 ~S4 ~S5 ~S6
~S17 ~S18 D ~S9 ~S11 ~S12 ~S13 ~S14 ~S15 ~S19 ~S3 ~S4 ~S5 ~S6
~S17 ~S18 D ~S9 ~S11 ~S12 ~S13 ~S14 ~S15 ~S19 ~S4 ~S5 ~S6
~S17 ~S18 D ~S9 ~S11 ~S12 ~S13 ~S14 ~S15 ~S19 ~S5 ~S6
~S17 ~S18 D ~S9 ~S11 ~S12 ~S13 ~S14 ~S15 ~S19 ~S6
~S17 ~S18 D ~S9 ~S11 ~S12 ~S13 ~S14 ~S15 ~S19
~S17 ~S18 D ~S11 ~S12 ~S13 ~S14 ~S15 ~S19
~S17 ~S18 D ~S12 ~S13 ~S14 ~S15 ~S19
~S17 ~S18 D ~S13 ~S14 ~S15 ~S19
~S17 ~S18 D ~S14 ~S15 ~S19
~S17 ~S18 D ~S15 ~S19

79
~S17 ~S18 D ~S19
~S18 D ~S19
D ~S19
D
20. The resulting axiom was then paired to clause 21, resulting to a contradiction which is
(D) (~ D)
∴ the argument is valid.
The Resolution Tree
Figure 5.10 Resolution Tree for Diagnosing Parasitic Worms

80
5.4.2 Session Run-through
In this section, a session run-through is presented to show the flow of the system in
diagnosing a disease, specifically gastroenteritis. The user interface in prescribing herbal
remedy is also shown.
Figure 5.11 Body Temperature Figure 5.12 Type of Bowel Movement
Figure 5.11 shows a prompt where the user needs to input the patient
temperature. Patient temperature is needed since in rule #1, the patient temperature is a
condition. With 38.0 as the patient’s temperature, then this implies that the patient has a
fever. Which drives the system to rule #5. Shown in figure 5.12 is a prompt where the
user needs to input the type of bowel movement of the patient. The type of bowel
movement is needed since it is a condition in rule # 5.

81
Figure 5.13. Abdominal Pain Figure 5.14. Bowel Evacuation
Figures 5.13 and 5.14 shows the prompt for the user to input if the patient has
abdominal pain and if the patient has experienced sensation of incomplete bowel
evacuation, in which the values of the parameters involed are needed in rule #5.
Figure 5.15. Obstruction Figure 5.16 More information for
Obstruction
Figures 5.15 shows a prompt where the user needs to input if the patient has experienced
obstruction and in figure 5.16 is the infolink page of the prompt.

82
Figure 5.17. Bloated Figure 5.18. More information for Bloated
Feeling
Figures 5.17 shows a prompt where the user needs to input if the patient has
bloated feeling and in figure 5.18 is the infolink page of the prompt.
Figure 5.19. Frequent discharge of
Figure 5.20. More information of frequent
discharge of intestinal gas or fart

83
Figures 5.19 shows a prompt where the user needs to input if the patient has
frequent discharge of intestinal gas and in figure 5.20 is the infolink page of the
prompt.
Figure 5.21. Gastroentiritis
Figure 5.21 shows the conclusion of the session which states that the patient has
gastroentiritis, based on the inputted value of the parameters by the user. It also shows
the herbal remedies for the disease.
Figure 5.22. Lemon Grass 1 Figure 5.23. Lemon Grass 2

84
Figures 5.22 and 5.23 shows the procedure and the dosage of the herbal remedy lemon
grass.
5.4.3 Evaluation
The following subsections shows the results based on the evaluation conducted to
the users and the domain experts.
5.4.3.1 Domain Experts’ Evaluation
Based on the domain experts’ feedbacks , the system can be used to provide basic
medical services in remote areas.
Below are th comments of the domain experts.
“ The system could be relied on in terms of seeking for an answer foru your
health problems especially when people living around ain’t got the knowledge of
such a complaint/problem.”
“ The system may help out friends living in rural areas gain access to seek
consults if incase medical personnel may not be available.”
5.4.3.2 Users’ Evaluation
For the user evaluation, the developer’s conducted testings to test the usefulness
and reliability of the system. Four users were involved during the testing.
During the testing, the users were asked to input the symptoms of a certain disease
that they have experienced. The system’s output in diagnosing was then compared to the
real disease expected by the user.

85
Based on the test results , three out of the four testers got the outputted disease the
same as the real disease expected. Based on the users’ comments, the system is useful for
people living in areas where there are no available medical practitioners and also in times
where there are no available means of transportation that can be used to go to hospitals and
clinics. The users also commented that the system is good since it promotes the use of
herbal medicines. When, they were asked if they’ll use it, the feedbacks are positive.
5.5 Documentation Phase
After the development of the expert system, a document produced containing the
details and discussions of the whole development process. The produced document
contains the needed information for the users and developer. Details, discussions and
outputs in each task done were also documented.
5.6 Maintenance Phase
After testing the system, necessary changes were made based on the
comments and suggestions of the domain experts. Rules were added to enhanced the
system.

86
Chapter 6
Conclusion and Recommendations
This chapter presents the conclusion and recommendations from the result of this
study.
6.1 Conclusion
The developed expert system using Android phones diagnoses and prescribes
herbal remedies. It can be used to provide alternative health care in the absence of medical
health practitioners. It provides mobility which means, it can used anytime and anywhere.
Subsequent to developing the expert system, the problem was identified and
justified. Knowledge of the domain experts in diagnosing and prescribing were then
acquired through interactive interviews with the domain expert and book referrals. The
acquired knowledge analyzed. With the analyzed acquired knowledge, rules were designed
and stored in the knowledge base. The correctness of these rules were tested through
resolution principle. After the initial development of the system, it was then presented to
the domain experts for verification and validation Based on the comments and
recommendations of the experts, the system was enhanced and improved. The objectives
were successfully met.
Also, the developed expert system is an answer to the assessed problems. The first
problem is the inadequacy of the delivery of health services to remote areas. The developed
system has the ability to diagnose and prescribe herbal remedies using Android phones,
which implies its mobility, which also means that people from remote areas can use the

87
developed expert system as an alternative in case where there is no available health service.
The second assessed problem is the unfamiliarity of the use and the administration of herbal
medicines to the people in remote areas. The developed expert system provides
instructions and useful information regarding the use and administration of herbal
medicines, thus this implies that the developed expert system is a solution to the assessed
problem.
In summary, the objective of the study were met and the problem was well
addressed with this solution.
6.2 Recommendations
The developed expert system for prescribing herbal remedies using java-enabled
phones has been proved to be useful in diagnosing health problems and prescribing herbal
remedies. It is then recommended that:
 A version of the system in native language such as Filipino, Visayan, Maranao
should be made.
 Locations and availability of the prescribed herbal should also be added in the
prescription phase of the system.
 If ever there are updates on the selected, approved herbal plants, it should also be
reflected in the system.
 The future researchers could use another shell which can be used in Java-enabled
phones.

89
APPENDIX A: Glossary of Terms

90
Glossary of Terms
In this study, the following terms are mostly used in the discussion. These terms
will help in better understanding.
Backward Chaining (goal-driven) – is a kind of system for the inference engine, which
processed first the hypothesis or solution or goal and keep looking for rules that
would allow to conclude that hypothesis (Abraham, 2005).
Domain Expert – provides the knowledge of the problem area, generally someone who
has worked in the domain area and understands its problem-solving techniques
(Luger, 2005).
Expert System – a model and associated procedure that exhibits, within a specific domain,
a degree of expertise in problem solving that is comparable to that of a human
expert (Chakraborty, 2010).
Expert System Shell – a piece of software which contains the user interface, a format for
declarative knowledge in the knowledge base, and an inference engine
(Chakraborty, 2010).
Forward Chaining (data-driven) – is a kind of system for the inference engine, which
processed first the initial facts and keep using the rules to draw new conclusions
given those facts (Abraham, 2005).
Herbal Actions – are due in part to herbal active constituents, this are special chemicals
and combination of chemicals and oils that are present in each particular plant.

91
Inference Engine – is the code at the core of the system which derives recommendations
from the knowledge base and problem-specific data in working storage
(Chakraborty, 2010).
Information and Communication Technology (ICT) – refers to the integration of
telecommunications, computers, middleware and the data systems that support,
store and transmit unified communications between systems (Murray, 2011).
Knowledge Acquisition – is a phase of the knowledge engineering methodology that
requires a significant degree of interaction between the knowledge engineer and the
specialist (Emberey et. al., 2007).
Knowledge Base – contains both factual and heuristics knowledge, it is a representation
of expertise, wisdom or rules-of-thumb, often represented by rules containing “if-
then-else” conditional statements or cases containing various fact patterns, in short
it is where knowledge of the domain expert is stored in a form of rules (Engelmore
and Feigenbaum, 1993).
Knowledge Engineer – primary involved in building an expert system, they are the one
who encodes the expert’s knowledge in a declarative form that can be used by the
expert system (Chakraborty, 2010).
Knowledge Engineering – is the art of designing and building expert systems, it is both
an applied part of artificial intelligence and a part of computer science (Engelmore
and Feigenbaum, 1993).

92
Quack Doctor – Quackery, false representation of a substance, device or therapeutic
system as being beneficial in treating a medical condition, diagnosing a disease, or
maintaining a state of health (The Free Dictionary, 2012).
Rule-based Expert System – a type of expert system which contains information obtained
from a human expert, and represents that information in the form of rules, such as
IF-THEN (Liao, 2005).

93
APPENDIX B: The Knowledge Base

94
The Knowledge Base
REM HealthKnowledge.kb
PARAM [apptitle] = "Disease Identifier and Herbal Prescriber Expert System"
PARAM [disclaimer] = "This Expert System is an initial version of diagnosing and
prescribing herbal remedies."
PARAM [appsubtitle] = "by Dumalagan, Helaryn L. & Potestas, Diorey Q."
PARAM [bgcolor] = "#6CB9FF"
PARAM [promptcolor] = "#060606"
PARAM [promptsize] = "20"
PARAM [nologo] = "TRUE"
PARAM [titlecolor] = "#6700FF"
REM HealthKnowledge.kb
RULE [#1]
If [temp] >= 40
Then [Diagnosis] = "Patient is prone to convulsion. Patient's possible disease is not part
of the domain."
RULE [#2]
If [temp] > 37.5 and
[temp] <= 40
Then [fever] = true
RULE [#3]
If [temp] <= 37.5 and
[temp] >= 34
Then [fever] = false
RULE [#4]
If [temp] < 40 and
[temp] >= 34 and
[stool type] = "Frequent, loose, watery stools." and
[body weakness] = "Yes" and
[sunken eyeball] = "Yes" and
[abdominal pain] = "Yes"
Then [diarrhea symptoms] = true

95
RULE [#5]
If [temp] < 40 and
[temp] >= 34 and
[stool type] = "Infrequent, difficulty in having bowel movement." and
[abdominal pain] = "Yes" and
[incomplete bowel evacuation] = "Yes"
Then [constipation symptoms] = true
RULE [#6.1]
If [diarrhea symptoms] = true
Then [bowel movement problem] = true
RULE [#6.2]
If [constipation symptoms] = true
Then [bowel movement problem] = true
RULE [#7]
If [fever] = true and
[bowel movement problem] = true
Then [abdominal infection] = true
RULE [#8]
[itchy skin rashes] = "Yes"
Then [skin infection] = true
RULE [#9]
[headache] = "Yes"
Then [head infection] = true
RULE [#10]
If [runny nose question] = "Yes"
Then [runny nose] = true
RULE [#11]
[runny nose] = true and
[cough] = "Yes"
Then [blocked airway] = true

96
RULE [#12]
[strep throat] = "Yes" and
[swallowing difficulty] = "Yes"
Then [throat infection] = true
RULE [#13]
If [head infection] = true and
[strep throat] = "Yes"
Then [mouth problem] = true
RULE [#14]
If [abdominal infection] = true and
[obstruction] = "Yes"
Then [serious abdominal infection] = true
RULE [#15]
If [blocked airway] = true and
[mouth problem] = true
Then [cold] = true
RULE [#16]
If [mouth problem] = true and
[throat infection] = true and
[swollen lymph nodes] = "Yes"
Then [pharyngitis] = true
RULE [#17]
If [serious abdominal infection] = true and
[bloated feeling] = "Yes" and
[fart] = "Yes"
Then [Diagnosis] = "GASTROENTERITIS"
RULE [#18]
If [abdominal infection] = true and
[tenesmus] = "Yes"
Then [Diagnosis] = "DYSENTERY"
RULE [#19]

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