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Shashank Mahajan, Gaurav Shrivastava / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 3, Issue 4, Jul-Aug 2013, pp.2229-2231
2229 | P a g e
Effective Diagnosis of Diseases through Symptoms Using Artificial
Intelligence and Neural Network
Shashank Mahajan*, Gaurav Shrivastava**
*(Research Scholar, Department of Information Technology, SVITS,Indore)
** (Asst. Professor, Department of Information Technology, SVITS,Indore)
ABSTRACT
In this Research paper is based on
artificial intelligence. Artificial Intelligence means
learn by knowledge. In this research mechanism
for artificial doctor that based on knowledge
based. This artificial doctor has the capability to
give possibilities of all diseases on the basis of
symptoms of patient. It’s like an assistant doctor
with more intelligent’s. This mechanism asks the
patient about the symptoms. On the basis of those
symptoms it will suggest about the possibilities of
diseases. This mechanism helps to doctor to
identify the disease of the patient. It will also ask
about the previous and family history. This
mechanism gave the result by studying the
previous treatment also, so it takes every
possibility of diseases. And it will also alert the
doctor for the medicine which cannot be given to
the patient.
Keywords – Artificial Neural Networks, General
Disease Diagnosis, Medical Diagnosis, Medical
Knowledge, Neural Networks
I. INTRODUCTION
MEDICAL diagnosis always has been an
art: we remember famous doctors as well as famous
painters or composers throughout the history. Again,
who is called an artist? A person who can carry out
something those others cannot, and that is exactly
what a good physician does during a medical
diagnosis procedure. He (or she) employs his
educations, experiences, and talent, to diagnose a
disease. A diagnosis procedure usually starts with the
patient complaints and the doctor learn more about
the patient situation interactively during an interview,
as well as by measuring some metrics such as blood
pressure or the body temperature. The diagnosis is
then determined by taking the whole available
patients status into the account. [1]
AI doctors different from human doctors
but they aren’t limited by human capacity. AI
doctors, having millions of points of data to draw on,
will remember where a human doctor might forget.
Because of this, they are in theory designed for more
accurate diagnosis. AI doctors also do not need to
sleep or eat and do not get sick themselves. This
means they can work 24/7, stay alert the whole time
and may cut costs for the hospital they work.
II. LITERATURE SURVEY
1.1 Hypertension is a disease that affects a wide
range of the population, particularly the elderly
after the age of 55. Hypertension is caused by
Blood Pressure. Blood Pressure is the force of
blood pushing against blood vessel walls. The
heart pumps blood into the arteries (blood
vessels), which carry the blood throughout the
body. If blood pressure is extremely high, there
may be certain symptoms such as Severe
headache, Fatigue, disorientation, Vision
problems, Chest pain, Difficulty in breathing,
irregular heartbeat and Blood in the urine .
Hypertension can cause Stroke, Heart failure,
Heart attack, Kidney failure and Vision
problems. Men have a greater likelihood of
developing high BP than women. This varies
according to age and among various ethnic
groups. In some cases, computer-based assisted
diagnoses have been claimed to be even more
accurate than those by clinicians. Predicting the
outcome of it is one of the most interesting and
challenging tasks in which a Neural Network
application is developed. Neural Networks are
well suited to problems that people use good at
solving but for which computers are not. Neural
Networks provide a very general way of
approaching problems.[2]
1.2 The diagnosis of diseases is a vital and intricate
job in medicine. The recognition of heart disease
from diverse features or signs is a multi-layered
problem that is not free from false assumptions
and is frequently accompanied by impulsive
effects. Thus the attempt to exploit knowledge
and experience of several specialists and clinical
screening data of patients composed in databases
to assist the diagnosis procedure is regarded as a
valuable option. This research work is the
extension of our previous research with
intelligent and effective heart attack prediction
system using neural network. A proficient
methodology for the extraction of significant
patterns from the heart disease warehouses for
heart attack prediction has been presented.
Initially, the data warehouse is pre-processed in
order to make it suitable for the mining process.
Once the preprocessing gets over, the heart
disease warehouse is clustered with
Shashank Mahajan, Gaurav Shrivastava / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 3, Issue 4, Jul-Aug 2013, pp.2229-2231
2230 | P a g e
the aid of the K-means clustering algorithm,
which will extract the data appropriate to heart
attack from the warehouse. Consequently the
frequent patterns applicable to heart disease are
mined with the aid of the MAFIA algorithm
from the data extracted. [3]
1.3 An artificial neural network in typical disease
diagnosis has been investigated. The real
procedure of medical diagnosis which usually is
employed by physicians was analyzed and
converted to a machine implementable format.
Then after selecting some symptoms of eight
different diseases, a data set contains the
information of a few hundred cases was
configured and applied to a MLP neural network.
The results of the experiments and also the
advantages of using a fuzzy approach were
discussed as well. Outcomes suggest the role of
effective symptoms selection and the advantages
of data fuzzificaton on a neural networks-based
automatic medical diagnosis system.[1]
III. MEDICAL DIAGNOSIS
PROBLEMS
The major task of medical science is to
prevent and diagnosis of the correct diseases. Here
our Focus is the second task, which as mentioned
before, is not a direct and simple task at all.[1]
 Generally doctor does not remember each and
everything. In some cases, sometimes doctor
takes the patient symptoms normally, they don’t
take much care about to identify the particular
disease and as they find the disease they are too
late to cure it.
 As consider, in some cases sometimes doctor or
the patient take the tumor normally and treat it
normally, as they find later that it is a cancer, at
that time it is too late to cure it. So it is a major
problem.
 The quality of diagnosis is totally depends on the
physician talent as well as his/her experiences.
[1]
 The training procedure of doctors, in particular
specialists, is a lengthy and expensive one. So
even in developed countries we may feel the lack
of MDs.
IV. PROPOSED SOLUTION
For This Mechanism We Are Giving The
Proposed Solution Flow Chart. In This Flow Chart.
We Are Considered All Possibility Of Condition Of
Patient. Its Helps According To Symptoms and
Identify The Disease.
Fig: Proposed Flow Chart
 Chief Complaint: - Chief complaint mean
major problem said by patient .Its 1st
priority of
major symptom. Ex. Fever, Loss of appetite,
Headaches, Chills, Cough, Abdominal pain,
Jaundice, Hair lost, Breathing Problem, Blood
in urine, Weight loss. Etc. [5]
 Asking general question, symptoms &
History of present illness:- According to chief
complaint asking general question and its
mechanism find out the other symptoms and
decide the priority of the symptoms
 Family History: - Some symptoms indicated to
the genetic diseases so asking family history its
help to conformation of particular diseases.
 Patient History:-In Some diseases required the
patient previous history because some
symptoms related to the previous history.
 Suggestion for Investigation:-According to
symptoms and analysis of real world data
collection of report its advice to investigation
.after the investigation report is may be correct
diagnosis of particular diseases.
 Computation of diseases: - Its phase
computation of Possibilities diseases using
Artificial intelligence (A.I.) And neural
network.
 Its computation base of real data collection and
history of previous data.
Shashank Mahajan, Gaurav Shrivastava / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 3, Issue 4, Jul-Aug 2013, pp.2229-2231
2231 | P a g e
After finalization of Possibilities diseases and also
asking to patient if any medicine is prohibited or bad
reaction to your body. It’s most important suggestion
to doctor giving medicines.
Searching of diseases based on symptoms
priority:-
We are giving another flow chart and work
on neural network, In this flow chart firstly we ask
patient symptoms and according to patient symptoms
we checked the highest priority of symptoms present
in those diseases. And some time some common
symptoms present more than one diseases. In this
condition for confirmation for accurate result we
suggested the investigation of related diseases.
Fig: Symptoms Priority Based Diseases Identify
V. CONCLUSION
Its mechanism help to identify the particular
diseases and In some Cases also identify the serious
diseases those not operate on O.P.D. level, its early
Identify as soon as cure and giving suggestion of
investigation and then it will clear the Diseases are
present or not and its mechanism also helpful for not
experienced doctors. And all general doctor and its
initially level also beneficial for general physician.
physician Feed the symptom and according to
symptoms identifies the disease. Its mechanism helps
doctor’s decision but can’t replace doctor position.
VI. ADVANTAGE
Its mechanism work as real time
environment it’s beneficial in following field-
 All Hospitals in O.P.D. level.
 General physician.
REFERENCES
[1] S. Moein, S. A. Monadjemi, and P.
Moallem, A Novel Fuzzy-Neural Based
Medical Diagnosis System, International
Journal of Biological and Medical Sciences
4:3, 2009, 146-150.
[2] B. Sumathi, Dr. A. Santhakumaran, Pre-
Diagnosis of Hypertension Using Artificial
Neural Network, Global Journal of
Computer Science and Technology Volume
11 Issue 2,2011
[3] Shantakumar B.Patil, Y.S.Kumaraswamy,
Intelligent and Effective Heart Attack
Prediction System Using Data Mining and
Artificial Neural Network, European
Journal of Scientific Research, Vol.31
No.4,2009,642-656“
[4] Florin Gorunesu, "Data Mining Techniques
in Computer-Aided Diagnosis: Non-
Invasive Cancer Detection," International
Journal of Bioengineering, Biotechnology
and Nanotechnology,Vol.1, No.2, pp.105 -
108, 2008.
[5] R. Silipo and C. Marchesi, "Artificial Neural
Network for automatic ECG analysis", IEEE
transactions on signal processing. . 46(5):
1417-1425.
[6] M.A. Tazi, S.Abir-Khalil, “Risk factors for
hypertension among the adult Moroccan
population”, Eastern Mediterranean health
journal, Vol. 15, No.4, 2009
[7] O. Er, N. Yumusak and F. Temurtas, "Chest
disease diagnosis using artificial neural
networks”, Expert Systems with
Applications, Vol.37, No.12, 2010, pp.7648-
7655.
[8] R. Lin, "An intelligent model for liver
disease diagnosis",Artificial Intelligence in
Medicine, Vol.47, No.1, 2009, pp. 53-62.
[9] D. Gil, M. Johnsson, J. M. Garicia Chemizo,
A S.Paya and D. R. Fernandez, "Application
of Artificial Neural Networks in the
Diagnosis of Urological Dysfunctions",
Expert Systems with Applications, Vol.36,
No.3, 2009,pp. 5754-5760
[10] “SAVILL’S SYSTEM OF CLINICAL
MEDICINE” BY E.C. WARNER.
[11] “COMMON MEDICAL SYMTOPMS” BY
P.J. MEHTA.
[12] GOULD’S POCKET MEDICAL
DICTIONARY.

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  • 1. Shashank Mahajan, Gaurav Shrivastava / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 4, Jul-Aug 2013, pp.2229-2231 2229 | P a g e Effective Diagnosis of Diseases through Symptoms Using Artificial Intelligence and Neural Network Shashank Mahajan*, Gaurav Shrivastava** *(Research Scholar, Department of Information Technology, SVITS,Indore) ** (Asst. Professor, Department of Information Technology, SVITS,Indore) ABSTRACT In this Research paper is based on artificial intelligence. Artificial Intelligence means learn by knowledge. In this research mechanism for artificial doctor that based on knowledge based. This artificial doctor has the capability to give possibilities of all diseases on the basis of symptoms of patient. It’s like an assistant doctor with more intelligent’s. This mechanism asks the patient about the symptoms. On the basis of those symptoms it will suggest about the possibilities of diseases. This mechanism helps to doctor to identify the disease of the patient. It will also ask about the previous and family history. This mechanism gave the result by studying the previous treatment also, so it takes every possibility of diseases. And it will also alert the doctor for the medicine which cannot be given to the patient. Keywords – Artificial Neural Networks, General Disease Diagnosis, Medical Diagnosis, Medical Knowledge, Neural Networks I. INTRODUCTION MEDICAL diagnosis always has been an art: we remember famous doctors as well as famous painters or composers throughout the history. Again, who is called an artist? A person who can carry out something those others cannot, and that is exactly what a good physician does during a medical diagnosis procedure. He (or she) employs his educations, experiences, and talent, to diagnose a disease. A diagnosis procedure usually starts with the patient complaints and the doctor learn more about the patient situation interactively during an interview, as well as by measuring some metrics such as blood pressure or the body temperature. The diagnosis is then determined by taking the whole available patients status into the account. [1] AI doctors different from human doctors but they aren’t limited by human capacity. AI doctors, having millions of points of data to draw on, will remember where a human doctor might forget. Because of this, they are in theory designed for more accurate diagnosis. AI doctors also do not need to sleep or eat and do not get sick themselves. This means they can work 24/7, stay alert the whole time and may cut costs for the hospital they work. II. LITERATURE SURVEY 1.1 Hypertension is a disease that affects a wide range of the population, particularly the elderly after the age of 55. Hypertension is caused by Blood Pressure. Blood Pressure is the force of blood pushing against blood vessel walls. The heart pumps blood into the arteries (blood vessels), which carry the blood throughout the body. If blood pressure is extremely high, there may be certain symptoms such as Severe headache, Fatigue, disorientation, Vision problems, Chest pain, Difficulty in breathing, irregular heartbeat and Blood in the urine . Hypertension can cause Stroke, Heart failure, Heart attack, Kidney failure and Vision problems. Men have a greater likelihood of developing high BP than women. This varies according to age and among various ethnic groups. In some cases, computer-based assisted diagnoses have been claimed to be even more accurate than those by clinicians. Predicting the outcome of it is one of the most interesting and challenging tasks in which a Neural Network application is developed. Neural Networks are well suited to problems that people use good at solving but for which computers are not. Neural Networks provide a very general way of approaching problems.[2] 1.2 The diagnosis of diseases is a vital and intricate job in medicine. The recognition of heart disease from diverse features or signs is a multi-layered problem that is not free from false assumptions and is frequently accompanied by impulsive effects. Thus the attempt to exploit knowledge and experience of several specialists and clinical screening data of patients composed in databases to assist the diagnosis procedure is regarded as a valuable option. This research work is the extension of our previous research with intelligent and effective heart attack prediction system using neural network. A proficient methodology for the extraction of significant patterns from the heart disease warehouses for heart attack prediction has been presented. Initially, the data warehouse is pre-processed in order to make it suitable for the mining process. Once the preprocessing gets over, the heart disease warehouse is clustered with
  • 2. Shashank Mahajan, Gaurav Shrivastava / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 4, Jul-Aug 2013, pp.2229-2231 2230 | P a g e the aid of the K-means clustering algorithm, which will extract the data appropriate to heart attack from the warehouse. Consequently the frequent patterns applicable to heart disease are mined with the aid of the MAFIA algorithm from the data extracted. [3] 1.3 An artificial neural network in typical disease diagnosis has been investigated. The real procedure of medical diagnosis which usually is employed by physicians was analyzed and converted to a machine implementable format. Then after selecting some symptoms of eight different diseases, a data set contains the information of a few hundred cases was configured and applied to a MLP neural network. The results of the experiments and also the advantages of using a fuzzy approach were discussed as well. Outcomes suggest the role of effective symptoms selection and the advantages of data fuzzificaton on a neural networks-based automatic medical diagnosis system.[1] III. MEDICAL DIAGNOSIS PROBLEMS The major task of medical science is to prevent and diagnosis of the correct diseases. Here our Focus is the second task, which as mentioned before, is not a direct and simple task at all.[1]  Generally doctor does not remember each and everything. In some cases, sometimes doctor takes the patient symptoms normally, they don’t take much care about to identify the particular disease and as they find the disease they are too late to cure it.  As consider, in some cases sometimes doctor or the patient take the tumor normally and treat it normally, as they find later that it is a cancer, at that time it is too late to cure it. So it is a major problem.  The quality of diagnosis is totally depends on the physician talent as well as his/her experiences. [1]  The training procedure of doctors, in particular specialists, is a lengthy and expensive one. So even in developed countries we may feel the lack of MDs. IV. PROPOSED SOLUTION For This Mechanism We Are Giving The Proposed Solution Flow Chart. In This Flow Chart. We Are Considered All Possibility Of Condition Of Patient. Its Helps According To Symptoms and Identify The Disease. Fig: Proposed Flow Chart  Chief Complaint: - Chief complaint mean major problem said by patient .Its 1st priority of major symptom. Ex. Fever, Loss of appetite, Headaches, Chills, Cough, Abdominal pain, Jaundice, Hair lost, Breathing Problem, Blood in urine, Weight loss. Etc. [5]  Asking general question, symptoms & History of present illness:- According to chief complaint asking general question and its mechanism find out the other symptoms and decide the priority of the symptoms  Family History: - Some symptoms indicated to the genetic diseases so asking family history its help to conformation of particular diseases.  Patient History:-In Some diseases required the patient previous history because some symptoms related to the previous history.  Suggestion for Investigation:-According to symptoms and analysis of real world data collection of report its advice to investigation .after the investigation report is may be correct diagnosis of particular diseases.  Computation of diseases: - Its phase computation of Possibilities diseases using Artificial intelligence (A.I.) And neural network.  Its computation base of real data collection and history of previous data.
  • 3. Shashank Mahajan, Gaurav Shrivastava / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 4, Jul-Aug 2013, pp.2229-2231 2231 | P a g e After finalization of Possibilities diseases and also asking to patient if any medicine is prohibited or bad reaction to your body. It’s most important suggestion to doctor giving medicines. Searching of diseases based on symptoms priority:- We are giving another flow chart and work on neural network, In this flow chart firstly we ask patient symptoms and according to patient symptoms we checked the highest priority of symptoms present in those diseases. And some time some common symptoms present more than one diseases. In this condition for confirmation for accurate result we suggested the investigation of related diseases. Fig: Symptoms Priority Based Diseases Identify V. CONCLUSION Its mechanism help to identify the particular diseases and In some Cases also identify the serious diseases those not operate on O.P.D. level, its early Identify as soon as cure and giving suggestion of investigation and then it will clear the Diseases are present or not and its mechanism also helpful for not experienced doctors. And all general doctor and its initially level also beneficial for general physician. physician Feed the symptom and according to symptoms identifies the disease. Its mechanism helps doctor’s decision but can’t replace doctor position. VI. ADVANTAGE Its mechanism work as real time environment it’s beneficial in following field-  All Hospitals in O.P.D. level.  General physician. REFERENCES [1] S. Moein, S. A. Monadjemi, and P. Moallem, A Novel Fuzzy-Neural Based Medical Diagnosis System, International Journal of Biological and Medical Sciences 4:3, 2009, 146-150. [2] B. Sumathi, Dr. A. Santhakumaran, Pre- Diagnosis of Hypertension Using Artificial Neural Network, Global Journal of Computer Science and Technology Volume 11 Issue 2,2011 [3] Shantakumar B.Patil, Y.S.Kumaraswamy, Intelligent and Effective Heart Attack Prediction System Using Data Mining and Artificial Neural Network, European Journal of Scientific Research, Vol.31 No.4,2009,642-656“ [4] Florin Gorunesu, "Data Mining Techniques in Computer-Aided Diagnosis: Non- Invasive Cancer Detection," International Journal of Bioengineering, Biotechnology and Nanotechnology,Vol.1, No.2, pp.105 - 108, 2008. [5] R. Silipo and C. Marchesi, "Artificial Neural Network for automatic ECG analysis", IEEE transactions on signal processing. . 46(5): 1417-1425. [6] M.A. Tazi, S.Abir-Khalil, “Risk factors for hypertension among the adult Moroccan population”, Eastern Mediterranean health journal, Vol. 15, No.4, 2009 [7] O. Er, N. Yumusak and F. Temurtas, "Chest disease diagnosis using artificial neural networks”, Expert Systems with Applications, Vol.37, No.12, 2010, pp.7648- 7655. [8] R. Lin, "An intelligent model for liver disease diagnosis",Artificial Intelligence in Medicine, Vol.47, No.1, 2009, pp. 53-62. [9] D. Gil, M. Johnsson, J. M. Garicia Chemizo, A S.Paya and D. R. Fernandez, "Application of Artificial Neural Networks in the Diagnosis of Urological Dysfunctions", Expert Systems with Applications, Vol.36, No.3, 2009,pp. 5754-5760 [10] “SAVILL’S SYSTEM OF CLINICAL MEDICINE” BY E.C. WARNER. [11] “COMMON MEDICAL SYMTOPMS” BY P.J. MEHTA. [12] GOULD’S POCKET MEDICAL DICTIONARY.