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Symbiosis Institute of Technology
Mtech Computer Science
Final year Project
Literature Review
By
Girmachew Gulint
Faculity Guides
Kalyani Kadam Mam &
Rahul Raghvendra sir
12/4/2017 Expert system recommend Diabetic patiens 1
Expert system to suggest a natural drink to the
diabetic patient to control blood sugar level in
order to recommend an ice cream
Problem of statement
From many reason of diabetes one is unbalanced meal. And this disease is the cause of many diseases such
as vision problem , kidney disease , stroke problem and others. If it gets into high and no treated well will
leads to death and also affects all human being.
12/4/2017
Expert system recommend Diabetic
patients
2
Introduction
Expert system :- “a piece of software which uses databases of expert knowledge to offer advice or make
decisions in such areas as medical diagnosis.”
Diabetes is a chronic(lifelong) disease marked by high levels of sugar in the blood (pancreas does not produce
enough insulin to properly control blood sugar levels).
 Three types of diabetic I ,II & Gestational
 age group
 cause and effect (toxicity and /or deficiency ) carbohydrate and insulin
 However can manage diabetes by diet management and physical exercise .
Analytic Hierarchy Process (AHP) is one of Multi Criteria decision making method that was originally developed
by Prof. Thomas L. Saaty. In short, it is a method to derive ratio scales from paired comparisons.
AHP is currently use in different fields such as :
 Agriculture
 Business
 Engineering
 Health
 Artificial Intelligent
 Expert System , to develop best questionnaire etc.
AHP has it own steps to achieve the goal.
AHP
Create a decision hierarchy by breaking down the
problem into a hierarchy of decision elements.
Collect input by a pair wise comparison of decision
elements.
Determine whether the input data satisfies a consistency
test. If it does not, go back to Step 2 and redo the pair
wise comparisons.
Calculate the relative weights of the decision elements.
Aggregate the relative weights to obtain scores and
hence rankings for the decision alternatives.
12/4/2017
Expert system recommend Diabetic
patients
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Motivation
• Humanity : myth , diabetic person can’t eat sweat food and drink.
• Number of patients will be 552million by 2030 .(www.dietdoctor.com)
• Complications /risk factors (stroke, Blindness , Heart Disease , Kidney disease , Nerve damage , Leg & foot
amputations and Death ).
• Cost : one single year insulin consumption may easily cost $2000 or more.
• Can control: by managing diet (drink ) and physical exercise.
12/4/2017
Expert system recommend Diabetic
patients
4
Literature Review
1. Suhas Machhindra Gaikwad , Dr. Preeti Mulay and Rahul Raghvendra Joshi (2015)[1] recommend ice cream to
diabetic patient by calculating the weight ,consistency index and ratio to rank it and match with patients blood
glucose level. Verified by AHP and MATLAB.
2. Ibrahim Mohammed Ahmed (2015)[2] develop knowledge based system for diabetes type2 daily meal
recommendation system of Sudanese. But does not consider blood sugar level of the patients.
3. Ibrahim M. Ahmed and Abeer M. Mahmoud (2014)[3] develop rule based expert system for diabetic patients to
recommend daily meal by considering patients IBM, activity ,weight and health status. This recommendation is
almost similar above NO paper. Using IBM is not good than blood sugar level to recommend diabetic patients.
4. Ludovic-Alexandre Vidal, Franck Marle and Jean-Claude Bocquet (2010)[4] thay proposed AHP to measure the
project complexity and consider multiple criterion. Overcome the problems such as reliability ,intuitive and user
friendly ,globally independent of project module and rank the projects.
5. Ludovic-Alexandre Vidal , Franck Marle and Jean-Claude Bocquet(2010)[5] refining frame work of Delphi
methodology and use AHP to rank the projects.
6. Audrey Mbogho, Joel Dave and Kulani Makhubele [6] develop prototype of expert system to diabetic patients
which asks question from users and after this system get enough information out put diabetic advice and
descriptions. Methodology they use was iterative system development methodology.
7. K.G.Viswanadhan [7] apply AHP to select best questionnaire by considering multiple conditions for effectiive
decision making.
12/4/2017
Expert system recommend Diabetic
patients
5
Continued
N
O
Author Title Public
ation
Year
Methodology
1 A, Suhas Machhindra Gaikwad
B, Dr. Preeti Mulay
C, Rahul Raghvendra Joshi
Symbiosis ,pune ,India
Analytical Hierarchy Process to
Recommend an Ice Cream to a
Diabetic Patient based on Sugar
Content in it
2015 AHP
2 Ibrahim Mohammed Ahmed
(Sudanese), PhD student
Egypt, Cairo
Daily Meal Planner Expert System for
Diabetics Type-2
2015 Semantic
network, rule
based and frame
based
representation
3 A, Ibrahim M. Ahmed
B, Abeer M. Mahmoud
Computer Science Department
Faculty of Computer and Information
Sciences
Ain Shams University, Cairo, Egypt
Development of an Expert System for
Diabetic Type-2
Diet
2014 Qualitative
research
methodology ,
rule based
representation
4 A, Ludovic-Alexandre Vidal
B, Franck Marle
C, Jean-Claude Bocquet
Measuring project complexity using
the Analytic Hierarchy Process
2010 AHP
12/4/2017 Expert system recommend Diabetic patiens 6
Continued
N
O
Author Title Publication
Year
Methodology
5 Ludovic-Alexandre
Vidal , Franck Marle,
Jean-Claude Bocquet
Using a Delphi process and the
Analytic Hierarchy Process (AHP)
to evaluate the complexity of
projects
tEcole Centrale Paris, Laboratoire
Genie Industriel, Grande Voie des
Vignes, 92290 Chatenay-Malabry,
France
2010 AHP
6 A, Audrey Mbogho
B, Joel Dave
C, Kulani Makhubele
Diabetes Advisor – A Medical
Expert System for Diabetes
Management
Cap Town
Rule based , IF-THEN
7 K.G.Viswanadhan How to get responses for multi-
criteria decisions in engineering
education–an ahp based approach
for
Selection of measuring instrument
AHP
12/4/2017 Expert system recommend Diabetic patiens 7
Proposed Solution
First of all this paper different form the base paper is here applying AHP for combined multiple alternative and
criterion decision making . Second extend their future work by clustering of ice cream and patients blood
group. In short describes as the following:
1] Prepare different combinations of drinks for recommending an ice cream to a diabetic patient and rank them
using AHP.
2] Then use System Dynamics modeling to judge recovery rate of diabetic patient with respect to the proper
drink and recommended ice cream.
3] Lastly, make use of clustering - device a new algorithm where you can show how you can map a specific
drink, ice cream with blood glucose level of a diabetic patient.
• Apply AHP to achieve combined objectives
• System dynamics : is an approach to understanding the nonlinear behaviour of complex systems over time
using frameworks and flows, internal feedback loops and time delays
• Clustering
– I will use five criterion and five alternatives for both
– With new algorithm and lower computation cost
Creating awareness and advices such as what are the symptoms , how to manage with natural drink .
12/4/2017 Expert system recommend Diabetic patiens 8
Work flow
Alternative and
Criterion
specifocation
AHP System Dynamics Clustering
12/4/2017
Expert system recommend Diabetic
patients
9
Proposed AHP
Recommend Ice cream and
natural drink for diabetic patient
Factor A Factor B Factor C Factor D Factor E
Ice Cream 1
Ice Cream 2
Ice Cream 3 Ice Cream 4
Ice Cream 5
ND1 ND2 ND3 ND4 ND5
Level 0
Level 1
Level 2
Level 3
12/4/2017 Expert system recommend Diabetic patiens 10
Ranking Mechanism
• Construct pairwise comparison of criterion and alternatives.
• Calculate weight of criterion and alternatives
• Calculate eigen vector and eigen value
• Calculate consistency index
• Calculate consistency ratio
• Then check the CR and verify the above calculations.
12/4/2017
Expert system recommend Diabetic
patients
11
Conclusion
I hope we had good discussion about diabetic its cause , symptoms , types and controlling
mechanisms. Moreover, combined AHP, pairwise comparison ,weight and consistency. Lastly ,
dynamic system model and clustering.
12/4/2017 Expert system recommend Diabetic patiens 12
Work break down
No Activity Time
1 Problem Definition and AHP Until end of October
2 System Dynamics November and December
3 Clustering February and March
4 Paper April
12/4/2017 Expert system recommend Diabetic patiens 13
References
1.Suhas Machhindra Gaikwadᵃ⃰,Dr. Preeti Mulayᵇ, Rahul Raghvendra Joshiᶜ(2015).” Analytical Hierarchy Process to Recommend an
Ice Cream to a Diabetic Patient based on Sugar Content in it”. www.sciencedirect.com. Department of Computer Science and IT,
Symbiosis Institute of Technology, Pune - 412 115, India
2. Ibrahim Mohammed Ahmed (Sudanese), PhD student (June 1-3, 2015).” Daily Meal Planner Expert System for Diabetics Type-2”
Department of Computer Science Egypt , Cairo
3. Audrey Mbogho1, Joel Dave2, and Kulani Makhubele. “Diabetes Advisor – A Medical Expert System for Diabetes Management ”.
University of Cape Towns
4.Ibrahim M. Ahmed, Abeer M. Mahmoud.(Volume 107 – No.1, December 2014).” Development of an Expert System for Diabetic
Type-2 Diet “. Department of Computer Science ,Ain Shams University, Cairo, Egypt
5. Ludovic-Alexandre Vidal , Franck Marle and Jean-Claude Bocquet (2010)[5] “Using a Delphi process and the Analytic Hierarchy
Process (AHP) to evaluate the complexity of projects tEcole Centrale Paris, Laboratoire Genie Industriel, Grande Voie des Vignes,
92290 Chatenay-Malabry, France »
6. Audrey Mbogho , Joel Dave and Kulani Makhubele “Diabetes Advisor – A Medical Expert System for Diabetes Management
“Cap Town
7. K.G.Viswanadhan “How to get responses for multi-criteria decisions in engineering education–an ahp based approach for
Selection of measuring instrument ”
• www.webmd.com
• www.dietdoctor.com/diabetes
• www.livestrong.com
12/4/2017 Expert system recommend Diabetic patiens 14
Thank you!
Question & suggestion??
12/4/2017
Expert system recommend Diabetic
patients
15

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360364350 expert-system-to-suggest-a-natural-drink-to-1

  • 1. Symbiosis Institute of Technology Mtech Computer Science Final year Project Literature Review By Girmachew Gulint Faculity Guides Kalyani Kadam Mam & Rahul Raghvendra sir 12/4/2017 Expert system recommend Diabetic patiens 1
  • 2. Expert system to suggest a natural drink to the diabetic patient to control blood sugar level in order to recommend an ice cream Problem of statement From many reason of diabetes one is unbalanced meal. And this disease is the cause of many diseases such as vision problem , kidney disease , stroke problem and others. If it gets into high and no treated well will leads to death and also affects all human being. 12/4/2017 Expert system recommend Diabetic patients 2
  • 3. Introduction Expert system :- “a piece of software which uses databases of expert knowledge to offer advice or make decisions in such areas as medical diagnosis.” Diabetes is a chronic(lifelong) disease marked by high levels of sugar in the blood (pancreas does not produce enough insulin to properly control blood sugar levels).  Three types of diabetic I ,II & Gestational  age group  cause and effect (toxicity and /or deficiency ) carbohydrate and insulin  However can manage diabetes by diet management and physical exercise . Analytic Hierarchy Process (AHP) is one of Multi Criteria decision making method that was originally developed by Prof. Thomas L. Saaty. In short, it is a method to derive ratio scales from paired comparisons. AHP is currently use in different fields such as :  Agriculture  Business  Engineering  Health  Artificial Intelligent  Expert System , to develop best questionnaire etc. AHP has it own steps to achieve the goal. AHP Create a decision hierarchy by breaking down the problem into a hierarchy of decision elements. Collect input by a pair wise comparison of decision elements. Determine whether the input data satisfies a consistency test. If it does not, go back to Step 2 and redo the pair wise comparisons. Calculate the relative weights of the decision elements. Aggregate the relative weights to obtain scores and hence rankings for the decision alternatives. 12/4/2017 Expert system recommend Diabetic patients 3
  • 4. Motivation • Humanity : myth , diabetic person can’t eat sweat food and drink. • Number of patients will be 552million by 2030 .(www.dietdoctor.com) • Complications /risk factors (stroke, Blindness , Heart Disease , Kidney disease , Nerve damage , Leg & foot amputations and Death ). • Cost : one single year insulin consumption may easily cost $2000 or more. • Can control: by managing diet (drink ) and physical exercise. 12/4/2017 Expert system recommend Diabetic patients 4
  • 5. Literature Review 1. Suhas Machhindra Gaikwad , Dr. Preeti Mulay and Rahul Raghvendra Joshi (2015)[1] recommend ice cream to diabetic patient by calculating the weight ,consistency index and ratio to rank it and match with patients blood glucose level. Verified by AHP and MATLAB. 2. Ibrahim Mohammed Ahmed (2015)[2] develop knowledge based system for diabetes type2 daily meal recommendation system of Sudanese. But does not consider blood sugar level of the patients. 3. Ibrahim M. Ahmed and Abeer M. Mahmoud (2014)[3] develop rule based expert system for diabetic patients to recommend daily meal by considering patients IBM, activity ,weight and health status. This recommendation is almost similar above NO paper. Using IBM is not good than blood sugar level to recommend diabetic patients. 4. Ludovic-Alexandre Vidal, Franck Marle and Jean-Claude Bocquet (2010)[4] thay proposed AHP to measure the project complexity and consider multiple criterion. Overcome the problems such as reliability ,intuitive and user friendly ,globally independent of project module and rank the projects. 5. Ludovic-Alexandre Vidal , Franck Marle and Jean-Claude Bocquet(2010)[5] refining frame work of Delphi methodology and use AHP to rank the projects. 6. Audrey Mbogho, Joel Dave and Kulani Makhubele [6] develop prototype of expert system to diabetic patients which asks question from users and after this system get enough information out put diabetic advice and descriptions. Methodology they use was iterative system development methodology. 7. K.G.Viswanadhan [7] apply AHP to select best questionnaire by considering multiple conditions for effectiive decision making. 12/4/2017 Expert system recommend Diabetic patients 5
  • 6. Continued N O Author Title Public ation Year Methodology 1 A, Suhas Machhindra Gaikwad B, Dr. Preeti Mulay C, Rahul Raghvendra Joshi Symbiosis ,pune ,India Analytical Hierarchy Process to Recommend an Ice Cream to a Diabetic Patient based on Sugar Content in it 2015 AHP 2 Ibrahim Mohammed Ahmed (Sudanese), PhD student Egypt, Cairo Daily Meal Planner Expert System for Diabetics Type-2 2015 Semantic network, rule based and frame based representation 3 A, Ibrahim M. Ahmed B, Abeer M. Mahmoud Computer Science Department Faculty of Computer and Information Sciences Ain Shams University, Cairo, Egypt Development of an Expert System for Diabetic Type-2 Diet 2014 Qualitative research methodology , rule based representation 4 A, Ludovic-Alexandre Vidal B, Franck Marle C, Jean-Claude Bocquet Measuring project complexity using the Analytic Hierarchy Process 2010 AHP 12/4/2017 Expert system recommend Diabetic patiens 6
  • 7. Continued N O Author Title Publication Year Methodology 5 Ludovic-Alexandre Vidal , Franck Marle, Jean-Claude Bocquet Using a Delphi process and the Analytic Hierarchy Process (AHP) to evaluate the complexity of projects tEcole Centrale Paris, Laboratoire Genie Industriel, Grande Voie des Vignes, 92290 Chatenay-Malabry, France 2010 AHP 6 A, Audrey Mbogho B, Joel Dave C, Kulani Makhubele Diabetes Advisor – A Medical Expert System for Diabetes Management Cap Town Rule based , IF-THEN 7 K.G.Viswanadhan How to get responses for multi- criteria decisions in engineering education–an ahp based approach for Selection of measuring instrument AHP 12/4/2017 Expert system recommend Diabetic patiens 7
  • 8. Proposed Solution First of all this paper different form the base paper is here applying AHP for combined multiple alternative and criterion decision making . Second extend their future work by clustering of ice cream and patients blood group. In short describes as the following: 1] Prepare different combinations of drinks for recommending an ice cream to a diabetic patient and rank them using AHP. 2] Then use System Dynamics modeling to judge recovery rate of diabetic patient with respect to the proper drink and recommended ice cream. 3] Lastly, make use of clustering - device a new algorithm where you can show how you can map a specific drink, ice cream with blood glucose level of a diabetic patient. • Apply AHP to achieve combined objectives • System dynamics : is an approach to understanding the nonlinear behaviour of complex systems over time using frameworks and flows, internal feedback loops and time delays • Clustering – I will use five criterion and five alternatives for both – With new algorithm and lower computation cost Creating awareness and advices such as what are the symptoms , how to manage with natural drink . 12/4/2017 Expert system recommend Diabetic patiens 8
  • 9. Work flow Alternative and Criterion specifocation AHP System Dynamics Clustering 12/4/2017 Expert system recommend Diabetic patients 9
  • 10. Proposed AHP Recommend Ice cream and natural drink for diabetic patient Factor A Factor B Factor C Factor D Factor E Ice Cream 1 Ice Cream 2 Ice Cream 3 Ice Cream 4 Ice Cream 5 ND1 ND2 ND3 ND4 ND5 Level 0 Level 1 Level 2 Level 3 12/4/2017 Expert system recommend Diabetic patiens 10
  • 11. Ranking Mechanism • Construct pairwise comparison of criterion and alternatives. • Calculate weight of criterion and alternatives • Calculate eigen vector and eigen value • Calculate consistency index • Calculate consistency ratio • Then check the CR and verify the above calculations. 12/4/2017 Expert system recommend Diabetic patients 11
  • 12. Conclusion I hope we had good discussion about diabetic its cause , symptoms , types and controlling mechanisms. Moreover, combined AHP, pairwise comparison ,weight and consistency. Lastly , dynamic system model and clustering. 12/4/2017 Expert system recommend Diabetic patiens 12
  • 13. Work break down No Activity Time 1 Problem Definition and AHP Until end of October 2 System Dynamics November and December 3 Clustering February and March 4 Paper April 12/4/2017 Expert system recommend Diabetic patiens 13
  • 14. References 1.Suhas Machhindra Gaikwadᵃ⃰,Dr. Preeti Mulayᵇ, Rahul Raghvendra Joshiᶜ(2015).” Analytical Hierarchy Process to Recommend an Ice Cream to a Diabetic Patient based on Sugar Content in it”. www.sciencedirect.com. Department of Computer Science and IT, Symbiosis Institute of Technology, Pune - 412 115, India 2. Ibrahim Mohammed Ahmed (Sudanese), PhD student (June 1-3, 2015).” Daily Meal Planner Expert System for Diabetics Type-2” Department of Computer Science Egypt , Cairo 3. Audrey Mbogho1, Joel Dave2, and Kulani Makhubele. “Diabetes Advisor – A Medical Expert System for Diabetes Management ”. University of Cape Towns 4.Ibrahim M. Ahmed, Abeer M. Mahmoud.(Volume 107 – No.1, December 2014).” Development of an Expert System for Diabetic Type-2 Diet “. Department of Computer Science ,Ain Shams University, Cairo, Egypt 5. Ludovic-Alexandre Vidal , Franck Marle and Jean-Claude Bocquet (2010)[5] “Using a Delphi process and the Analytic Hierarchy Process (AHP) to evaluate the complexity of projects tEcole Centrale Paris, Laboratoire Genie Industriel, Grande Voie des Vignes, 92290 Chatenay-Malabry, France » 6. Audrey Mbogho , Joel Dave and Kulani Makhubele “Diabetes Advisor – A Medical Expert System for Diabetes Management “Cap Town 7. K.G.Viswanadhan “How to get responses for multi-criteria decisions in engineering education–an ahp based approach for Selection of measuring instrument ” • www.webmd.com • www.dietdoctor.com/diabetes • www.livestrong.com 12/4/2017 Expert system recommend Diabetic patiens 14
  • 15. Thank you! Question & suggestion?? 12/4/2017 Expert system recommend Diabetic patients 15