ANOMALY PATTERN DETECTION OF AN OUTBREAK DISEASE USING RULE BASED SYSTEM USING MENINGITIS AS A CASE STUDY.

CHAPTER ONE: INTRODUCTION

1.1       Background of The Study                                                                          1

1.2       Statement of The Problem                                                                         3

1.3       Aim and Objectives of The Study                                                              3

1.4       Research Questions                                                                                   4

1.5       Scope of The Study                                                                                     4

1.6       Research Methodology                                                                              4

1.7       Significance of The Study                                                                         5

1.8       Limitations of The Study                                                                             6

 

CHAPTER TWO: LITERATURE REVIEW

2.1       Overview on Meningitis                                                                              7

2.1.1   How Meningitis is Transmitted                                                                  8

2.1.2   Symptoms of Meningitis                                                                             9

2.1.3   Risk Factors for Meningitis                                                                                    9

2.1.4   How is Meningitis Diagnosed                                                                   10

2.1.5   How is Meningitis Treated                                                                          11

2.1.6   Prevention of Meningitis                                                                            11

2.2       Anomaly Detection                                                                                      13

2.2.1   Rule Based Expert Systems (RBR)                                                          13

2.2.1.1 Theory of Rule-Based Systems                                                               14

2.2.1.2   Rule-Based Reasoning                                                                           15

2.3       Overview on Expert Advisor System                                                        16

2.3.1   The Structure of Medical Expert Systems                                               17

2.3.2   Rule Based Expert System                                                                        18

2.3.3   Knowledge Based Expert System                                                            18

2.4       Artificial Intelligence (AI) and Clinical Guidelines                                 19

2.4.1   Group Decision Making                                                                              19

2.5       Overview On Expert System                                                                      20

2.6       Computer-Interpretable Guidelines                                                          21

2.6.1   Clinical Expert Systems                                                                              22

2.6.2   Importance of Clinical Expert Systems                                                    23

2.6.3   Clinician Motivation To Use Expert Systems                                          24

2.7       The Concept on Rule Based Approach in Expert System                   25

2.7.1   Obtaining Information for Developing Rules                                          26

 

CHAPTER THREE: SYSTEM ANALYSIS AND DESIGN

3.1       Analysis of The Existing System                                                              27

3.2       Problem with The Existing System                                                           28

3.3       Analysis of The Proposed System                                                            28

3.4       Benefits of The Proposed System                                                            29

3.5       System Design                                                                                             29

3.5.1   Preliminary Design Stage                                                                          29

3.5.2   Structural Design Stage                                                                             30

3.5.3   Program Design                                                                                           30

3.5.4   Interface Design                                                                                          30

3.5.5   Input/Output Design                                                                                    30

3.5.6   Input Design                                                                                                 31

3.5.7   Output Design                                                                                              35

3.6       Data Flow Diagram                                                                                      37

3.7       Database and Structure of Table                                                              39

3.8.      Entity Relationship Diagrams                                                                    42

3.9       Proposed System with UML                                                                       43

3.10    The Algorithm of Rule Based Expert System                                         47

 

CHAPTER FOUR: PROGRAMMING AND DOCUMENTATION

4.1       System Implementation                                                                              48

4.1.1   Functional Requirement                                                                            48

4.1.2   Non-Functional Requirement                                                                   48

4.2       Justification of Programming Language Used                                       50

4.3       Operating Procedures                                                                                 51

4.3.1   Program Installation                                                                                                51

4.3.2   Programmer’s Guide to Maintenance                                                      51

4.3.3   Personnel and Procedure                                                                          52

4.4       User Guide to The System                                                                         52

4.4.1   Running the Program                                                                                 52

4.4.2   Program Specification and Sub Programs                                              52

4.4.3   Change over process                                                                                  53

4.5       Documentation of The System                                                                  53

4.6       Statistical Analysis                                                                                      54

4.7       Hypothesis Formulation/Result and Discussion                                               54

4.7.1   Hypothesis Testing                                                                                      57

 

CHAPTER FIVE: SUMMARY, CONCLUSION AND RECOMMENDATION

5.1       Summary                                                                                                       60

5.2       Conclusion                                                                                                   61

5.3       Recommendation                                                                                        62

            References                                                                                                   69

 

 

ABSTRACT

Detection of diseases are important, so as to stop them from infecting us. More so, outbreak diseases which cause epidemics. Traditional techniques for anomaly detection are unsatisfactory for this problem because they identify individual data points that are rare due to particular combinations of features. When applied to our scenario, these traditional algorithms discover isolated outliers of particularly strange events, such as an irrelevant event, that are not indicative of a new outbreak. Instead, we would like to detect anomalous patterns. These patterns are groups with specific characteristics whose recent pattern of illness is anomalous relative to historical patterns. We used a rule based anomaly detection algorithm that characterizes each anomalous pattern with a rule. The significance of each rule was carefully evaluated. Our algorithm is compared against a standard detection algorithm by measuring the number of false positives and the timeliness of detection. Simulated data, produced by a questionnaire that creates the effects of an epidemic on the respondent location, would be used for evaluation. The results outcomes indicate that our algorithm has significantly better detection times for common significance thresholds on meningitis.