ABSTRACT
This research work focused on the development of information system for malaria diagnosis using General hospital Ikot Ekpene. A fuzzy logic system is an artificial intelligence based system that involves drawing conclusion from a partial truth. The problems that necessitated the development of the system include: blood testing for diagnosis of malaria is time consuming and expensive, health care facility should be accessible by all at all times, medical expert maybe under pressure. In view of these problems, the objectives of the study included: to create a system that will help in diagnosis of malaria using fuzzy logic, to create a system to help simplify the task of a Doctor in diagnosing malaria, to create a system to improved efficiency by systematically keeping patient diagnosis records and timely generation. The software development methodology used is object oriented analysis and design methodology (OOADM). The programming language used is Visual BASIC and the database used is Microsoft Access 2003.
TABLE OF CONTENTS
Title Page – – – – – – – –
i
Certification – – – – – – – – – ii
Approval Page – – – – – – – – iii
Dedication – – – – – – – – iv
Acknowledgment – – – – – – – –
v
Abstract – – – – – – – –
vi
Table of Contents – – – – – – – – vii-ix
List of Figures – – – – – – – – x
List of Tables – – – – – – – xi
CHAPTER ONE: INTRODUCTION
1.0 Introduction
– – – – – – – 1
1.1 Background
of the Study – – – – – – 1-2
1.2 Statement
of Problem – – – – – 2-3
1.3 Aim
and Objectives of the Study – – – – 3
1.4 Significance
of the Study – – – – – – 3
1.5 Scope
of the Study – – – – – – – 4
1.6 Organization of Research – – – – – – 4
1.7 Definition of Terms – – – – – – 5
CHAPTER TWO: LITERATURE REVIEW
- Introduction – – – – – – – – 6
2.1 Theoretical Background – – – – 6-7
2.2 The Concept of Information System – – – 7-8
2.3 Malaria Parasite – – – – – – – 9-10
2.3.1 Signs and Symptoms – – – – – – – 10-11
2.3.2 Diagnosis – – – – – – 11-12
2.3.3 Treatment – – — – – – 12-13
2.4 Information Logic in Medical Decision Support Systems
2.5 Automated logic in Malaria Diagnosis – – 14-16
CHAPTER THREE: SYSTEM ANALYSIS AND
DESIGN
-
Introduction – – – – – – – 17
3.1 Research Methodology – – – – – 17
3.2
Analysis of the Existing System – – – – 17-18
3.2.1Advantages
of the Existing System – – – 18
3.2.2
Disadvantages of the Existing System – – – 18
3.3 Analysis of the Proposed System – – – – 18-20
3.3.1
Advantages of the Proposed system – – – 20
3.4 System Design – – – – – – – 20
3.4.1 Input
layout – – – – – – –
21
3.4.2 Output Layout – – 22
3.4.3 Algorithm – – 23
3.4.4 Program Flowchart – – 24-28
3.4.5 Database Design – – – – – 29
3.4.6 System Architecture – – – – – 30
3.4.7 Use Case/Class Diagram – – – – – — 30-32
CHAPTER FOUR: SYSTEM IMPLEMENTATION
4.0
Introduction – – – – – – – 33
4.1 System
Design Diagram – – – – – – 33
4.2 Choice
of Programming Language – – – 33
4.3 Analysis
of Modules – – – – – 34
4.4 Programming
Environment – – – – – 34
4.4.1 Hardware Requirements – – – – – 34
4.4.2 Software Requirements – – – – 34-35
4.5 System
Implementation – – – – – – 35
CHAPTER FIVE: SUMMARY, RECOMMENDATION
AND CONCLUSION
5.0 Introduction – – – – – – – 36
5.1 Constraints
of the Study – – – – – – 36
5.2 Summary – – – – – – 36-37
5.3 Conclusion – – – – – – 37
5.4 Recommendations – – – – – – 37
References – – – – – – 38
Appendix A (Source Code) – – – – – 39-42
Appendix B (Output) – – – – – – 43-48
LIST OF TABLES
Page
Number
Table
3.1: Patient Registration output layout – – – 22
Table
3.2: Diagnosis output layout- – – – – 22
LIST OF FIGURES
Page
Number
Fig. 2.1: Patient Registration form – – – – 7
Fig. 2.2: The Process of applying fuzzy logic in disease diagnosis 12
Fig. 3.1: Patient Registration input layout – – – – 21
Fig. 3.2: Fuzzy logic diagnosis layout – – – – – 21
Fig 3.3: Login flowchart – – – – – – – 24
Fig. 3.4: Main menu flowchart – – – – – – 25
Fig. 3.5: Patient registration flowchart – – – – 26
Fig. 3.6: Diagnosis flowchart – – – – – – 27
Fig. 3.7: Database Records – – – – – – 28
Fig. 3.8: Architecture of the System – – – – – 29
Fig. 3.9: Class diagram – – – – – – – 32
CHAPTER ONE
INTRODUCTION
- Introduction
This chapter presents the introduction
to the study on information system for malaria diagnosis. It presents the
introduction, background of the study, statement of the problem, aim and
objectives of the study, significance of the study, scope of the study,
organization of the research and definition of terms.
1.1 Background of the Study
Identification of malaria at early stage will be helpful as its effect increasing drastically and cause great harm to people life. Malaria is due to imbalance (increase) of amount of parasites in the patient’s blood and an indicator for the degree of infection. Malaria is caused by a blood parasite named Plasmodium spp. It affects at least 300 to 600 million people every year and causes an estimated 3 million deaths. Early diagnosis and treatment of it is necessary. Automated system for disease diagnosis is becoming popular day by day. In today’s world people are so busy, that they hardly have enough time to visit a doctor. So they can use the service of this expert diagnosis system residing home or office and have an idea about the disease. After that they can consult the specialist doctor if it is necessary or serious. Fuzzy logic algorithm can help in the early diagnosis of malaria when applied properly (Beth, Claudio and Burhan, 2002)
This research presents an information system for malaria patients. In this method, based on the selection of the problem area/ problem, the information system provides an interface for the user to input needed information. Based on the inputs, the user is again asked some questions. Depending on the answer inputted, the system diagnosis malaria based on its knowledge, add catalyst factor (if any), does ranking and gives the result (Adekoya, Akinwale and Oke, 2008).
Information
system for malaria patients can be used for solving problems. The information
system logic can be conceptualized as a generalization of classical logic.
Malaria diagnosis logic was developed by Lotfi Zadeh in the mid-1960s to model
those problems in which imprecise data must be used or in which the rules of
inference are formulated in a very general way making use of diffuse
categories. (Adekoya, Akinwale and Oke, 2008).
1.2 Statement of the Problem
The
following problems necessitated this study:
- Blood testing for diagnosis of malaria is time consuming and expensive.
- Health care facility should be accessible by all at all times. But some of the people that should access these facilities are far removed from these facilities.
- Medical Expert maybe under pressure.
- Medical expert maybe unsure of their diagnosis in which they may seek some more experience.
- Medical experts maybe slow in the process of diagnosing.
- Absence of a computer based system for malaria diagnosis
1.3
Aim and Objectives of the Study
The
major aim of this work is to develop an information system for the diagnosis of
malaria. The objectives of the study are:
It
is also to ascertain whether the diseases could be diagnosed based on signs and
symptoms.
- To
create a system that will help in diagnosis of malaria.
- To
create a system to help simplify the task of a Doctor in diagnosing malaria.
- To
create a system to improved efficiency by systematically keeping patient
diagnosis records and timely generation.
