Design and Implementation of a Medical Expert System

Design and Implementation of a Medical Expert System.

ABSTRACT            

Diseases must be treated healthy and on time. If they are not treated on time, they can escort to many health problems with these problems might become the reason of death.

These problems are becoming inferior due to the scarcity of specialists, health facilities and practitioners.

In an attempt to address such problems, studies ended attempts toward design and develop expert systems which can present advice for physicians and patients to make easy the diagnosis along with recommend treatment of patients.

This review paper represents a comprehensive study of medical expert systems used for diagnosis of various diseases. It provides a concise overview of medical diagnostic expert systems along with presents an analysis of already existing studies.

TABLE OF CONTENTS

TITLE PAGE     i

CERTIFICATION  ii

DEDICATION    iii

ACKNOWLEDGEMENT iv

ABSTRACT       v

TABLE OF CONTENTS        vi

LIST OF TABLES      vii

LIST OF FIGURES        viii

CHAPTER ONE:  INTRODUCTION

1.1          BACKGROUND OF THE STUDY     1

1.2          STATEMENT OF THE PROBLEM  2

1.3          AIM AND OBJECTIVES OF THE STUDY         2

1.4          METHODOLOGY      3

1.5          SIGNIFICANCE OF THE STUDY        3

1.6          SCOPE OF THE PROJECT          3

1.7          LIMITATION OF STUDY   4

1.8          DEFINITION OF TERMS/VARIABLES      4

CHAPTER TWO: LITERATURE REVIEW

2.0          INTRODUCTION     6

2.1          OVERVIEW OF EXPERT SYSTEM   6

2.2          MEDICAL EXPERT SYSTEMS     6

2.3          STRUCTURE OF MEDICAL EXPERT SYSTEMS   7

2.4          EXISTING MEDICAL EXPERT SYSTEMS      8

2.4.1      EXPERT SYSTEM FOR DIAGNOSIS OF INFLUENZA UNDER UNCERTAINTY       9

2.4.2      FUZZY EXPERT SYSTEM FOR DIAGNOSIS OF RISK OF HYPERTENSION        9

2.4.3      RULE BASED EXPERT SYSTEM FOR MEMORY LOSS DISEASE   10

2.4.4      FUZZY SYSTEM FOR DIAGNOSIS OF LIVER DISORDER        10

2.4.5      ARTIFICIAL NEURAL NETWORK FOR DIAGNOSIS OF HEART DISEASE       11

2.5          APPLICATION OF EXPERT SYSTEMS        11

2.5          HISTORY OF DELACK HOSPITALS    11

2.6          ORGANOGRAM OF DELACK HOSPITALS     12

CHAPTER THREE: RESEARCH METHODOLOGY

3.0          INTRODUCTION   13

3.1          ANALYSIS OF THE EXISTING SYSTEM     13

3.2          OVERVIEW OF THE PROPOSED SYSTEM     14

3.3          METHOD OF DATA COLLECTION      14

3.4          SYSTEM DESIGN    15

3.4.1      FLOWCHART     15

3.4.2      UML DIAGRAM       18

3.5          DATABASE STRUCTURE 19

3.5.1      OUTPUT STRUCTURE     19

3.5.2      INPUT STRUCTURE       20

CHAPTER FOUR: SYSTEM TESTING AND IMPLEMENTATION

4.0          INTRODUCTION       22

4.1          CHOICE OF PROGRAMMING LANGUAGE AND DATABASE     22

4.2          SYSTEM REQUIREMENT      22

4.2.1      HARDWARE REQUIREMENT AND SPECIFICATIONS    22

4.2.2      SOFTWARE REQUIREMENT AND SPECIFICATIONS  23

4.3          RESULT INTERFACE      23

4.4          SYSTEM TESTING AND IMPLEMENTATION     25

4.5          DESCRIPTION OF FINDINGS       27

4.6          SYSTEM DOCUMENTATION   28

4.6.1      HOW TO LOAD THE SOFTWARE   28

4.6.2      HOW TO RUN THE SOFTWARE  28

4.6.3      THE PLATFORM    28

CHAPTER FIVE:  SUMMARY, CONCLUSION AND RECOMMENDATION

5.1          SUMMARY      29

5.2          CONCLUSION   29

5.3          RECOMMENDATION       29

REFERENCES        31

INTRODUCTION

An expert system is a software system that attempts to reproduce the performance of one or more human experts, most commonly in a specific problem domain, and is a traditional application and/or subfield of artificial intelligence.

Expert systems may or may not have learning components but a third common element is that once the system is developed it is proven by being placed in the same real-world problem-solving situation as the human SME, typically as an aid to human workers or a supplement to some information system.

As a premier application of computing and artificial intelligence, the topic of expert systems has many points of contact with general systems theory, operations research, business process reengineering and various topics in applied mathematics and management science.

REFERENCES

Eugena & George (2009). The Diagnosis of Some Kidney Diseases in a PROLOG Expert System. Retrieved from https://www.researchgate.net/profile/Eugene_Roventa/publication/224593142_The_diagnosis_of_some_kidney_disease_in_a_small_prolog_Expert_System.pdf on June 27, 2018

Jimmy S (2013). The Diagnosis of Some Lung Diseases in a PROLOG Expert System. Retrieved from https://www.researchgate.net/publication/303699292_Implementation_of_an_Expert_System_for_Lung_Disease_Diagnosis on June 17, 2018.

Sammy, S & Abu, N (2008). An Expert System for Diagnosing Eye Diseases Using Clips. Retrieved from https://www.researchgate.net/publication/274258367_AN_EXPERT_SYSTEM_FOR_DIAGNOSING_EYE_DISEASES_USING_CLIPS on June 29, 2018

Hossain et al (2014).  Expert System for Diagnosis of Influenza under Uncertainty. Retrieved from https://www.academia.edu/8752752751/A_Belief_Rule-Based_Expert_System_to_Diagnose_Influenze on June 20, 2018

Azian et al (2001). Fuzzy Expert System for Diagnosis of Risk of Hypertension. Retrieved from https://pdfs.semanticscholar.org/b7ad/d498b2927d35640946c249158ede32d33f21f.pdf on July 1, 2018

Komal et al (2014). Rule Based Expert System for Memory Loss Disease. Retrieved from https://www.ijset.com/v1s3/IJISET_V1_13_12.pdf on July 2, 2018

Neshat et al (2008). Fuzzy Expert System Design for Diagnosis of Liver Disorders proceedings of Knowledge Acquisition and Modeling. Retrieved from https://www.researchgate.net/publication/228814316_Fuzzy_Expert_System_Design_for_Diagnosis_of_Liver_Disorder on June 27, 2018