COMP763 MSc Dissertation Example 2025 | LBU

Abstract

Diabetes Mellitus is still a global health challenge, with increasing prevalence rates necessitating advanced predictive methodologies for effective management and prevention. This research primaryfocus is on evaluating machine learning algorithms to predict diabetes in the United Kingdom, highlights the effect of the behavioural risk factors like smoking, blood pressure, and body mass index...........View More

TABLE OF CONTENTS

TITLE ..................................................................................................................... I
ACKNOWLEDGEMENTS ...................................................................................... II
ABSTRACT .......................................................................................................... III
LIST OF FIGURES .............................................................................................. VII
ABBREVIATIONS ................................................................................................. VIII

CHAPTER 1: INTRODUCTION .................................................................... 10
1.1 Overview ......................................................................................................... 10
1.2 Problem Statement ......................................................................................... 13
1.3 Aim and Objectives ......................................................................................... 13

CHAPTER 2: LITERATURE REVIEW ....................................................... 15
2.1 Global and UK Diabetes Prevalence and Impact .......................................... 15
2.2 Traditional Methods for Diabetes Diagnosis .................................................. 15
2.3 Predictive Models for Diabetes Using ML Techniques .................................. 15

CHAPTER 3: METHODOLOGY ................................................................. 20
3.1 Knowledge Discovery in Databases (KDD) ..................................................... 20
3.2 Ethical Considerations ................................................................................... 23

CHAPTER 4: RESULT / RESEARCH DESIGN AND IMPLEMENTATION .... 25
4.1 Introduction .................................................................................................... 25
4.2 Output ............................................................................................................ 26
4.3 Initialization and Training .............................................................................. 44
4.4 Plotting Decision Boundaries ......................................................................... 45
4.5 Insights ........................................................................................................... 45
4.6 Traditional Methods ....................................................................................... 46
4.7 Limitations of Each Technique Used ............................................................. 47

CHAPTER 5: DISCUSSION AND EVALUATION ....................................... 50
5.1 Overview of Dataset ...................................................................................... 50
5.2 Key Features of the Dataset .......................................................................... 50
5.3 Computational Efficiency and Scalability ...................................................... 53
5.4 Robustness and Generalization ..................................................................... 54
5.5 Discussing Their Implications ....................................................................... 55
    • Decision Tree: Clinical Interpretability and Actionability .............................. 56
5.6 Challenges of Implementation Work ............................................................. 57
    5.6.1 Data-Related Challenges ................................................................... 57
    5.6.2 Deployment Challenges ..................................................................... 57
5.7 Maintenance and Updating ........................................................................... 58
5.8 Comparative Analysis and Conclusion .......................................................... 59

CHAPTER 6: PROJECT MANAGEMENT .................................................. 60
6.1 Overview of the Project Management Approach ........................................... 60
6.2 Project Scope ................................................................................................. 61
6.3 Implementation and Execution ...................................................................... 62
6.4 Analysis and Interpretation ............................................................................ 62
6.5 Results Interpretation ..................................................................................... 62

CHAPTER 7: CONCLUSION AND RECOMMENDATION ......................... 63
7.1 Summary of Key Findings ............................................................................... 63
7.2 Recommendations ......................................................................................... 65
    7.2.1 Clinical Implementation ...................................................................... 65
    7.2.2 Future Research Directions ............................................................... 65
    7.2.3 Validation and External Testing ......................................................... 66
    7.2.4 Ethical and Privacy Considerations .................................................... 66

REFERENCES ................................................................................................. 68
APPENDICES .................................................................................................... 89

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