HEART DISEASE PREDICTION SYSTEM USING

RULES BASED TECHNIQUE

ASHADE BILAL OLALERE

BACHELOR OF COMPUTER SCIENCE

(SOFTWARE DEVELOPMENT)

UNIVERSITI SULTAN ZAINAL ABIDIN

2018

HEART DISEASE PREDICTION SYSTEM USING RULES

BASED TECHNIQUE

ASHADE BILAL OLALERE

BACHELOR OF COMPUTER SCIENCE (SOFTWARE DEVELOPMENT)

FACULTY OF INFORMATICS AND COMPUTING

UNIVERSITI SULTAN ZAINAL ABIDIN, TERENGGANU, MALAYSIA

2018

ii

DECLARATION

I hereby declare that this report is based on my original work except for quotations

and citations, which have been duly acknowledged. I also declare that it has not been

previously or concurrently submitted for any other degree at Universiti Sultan Zainal

Abidin or other institutions.

________________________________

Name : Ashade Bilal Olalere

Date : ..................................................

iii

CONFIRMATION

This is to confirm that:

The research conducted and the writing of this report was under my supervison.

________________________________

Name : Dr Nadiah Bint Zamri

Date : ..................................................

iv

DEDICATION

This thesis work is dedicated to my beloved Parents who have been a constant source

of support and encouragement during the challenges of graduate School and life. I am

truly thankful for having you in my life. This work is also dedicated to Brother

Lukman Olagoke, whose good examples have taught me to work hard for the things

that I aspire to achieve.

v

ABSTRACT

Every year over one million people died by suicide worldwide. 6.7% of them are due

to depression. High depression is one of the prevalent mental disorder problems. They

are less visible and can be continuously revised. Therefore, this study develops a

Mental Disorder Diagnosis and Stress Self Treatment System. This system offers users

with the set of a questionnaire to measure the stress, anxiety, and depression. The

questionnaire is generated using rule-based techniques. Besides, weighted sum

method is also used to calculate the sum of answer from the users. If the feedbacks

show the definite mental health problems, the users are given the stress self-treatment.

Also, this system can be used at all times and anywhere. Every year, over seventeen

million people died from heart disease worldwide. Heart disease is a general name for

conditions and disorders that affect the heart and the blood vessels. It can attack any

healthy people with no clues or sign, either young or old. They are less visible and can

be continuously revised. Therefore this study develops a Heart Prediction System.

This system is an end user support system and online consultation system. It allows

users to get the instant guidance about their heart issues through answering the set of

questionnaires about the heart disease. The system covers with various heart diseases

symptoms such as Angina, Arrhythmia, Atrial Fibrillation, Cardiomyopathy, Heart

failure, and heart attack. It allows the user to record their heart condition status and

guide them through the heart disease treatment. The questionnaire is generated using

data mining techniques. Also, this system can be used all times and anywhere.

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ABSTRAK

Setiap tahun lebih satu juta orang mati akibat bunuh diri di seluruh dunia. 6.7%

daripadanya disebabkan kemurungan. Kemurungan yang tinggi adalah salah satu

masalah gangguan mental yang lazim. Mereka kurang dapat dilihat dan boleh disemak

secara berterusan. Oleh itu, kajian ini membangunkan Diagnosis Gangguan Mental

dan Sistem Rawatan Diri Stres. Sistem ini menawarkan pengguna dengan set soal

selidik untuk mengukur tekanan, kebimbangan, dan kemurungan. Soal selidik dijana

menggunakan teknik berasaskan peraturan. Di samping itu, kaedah nilai tertimbang

juga digunakan untuk mengira jumlah jawapan daripada pengguna. Jika maklum balas

menunjukkan masalah kesihatan mental yang jelas, para pengguna diberi rawatan diri

tekanan. Juga, sistem ini boleh digunakan setiap saat dan di mana sahaja. Setiap tahun,

lebih daripada tujuh belas juta orang mati akibat penyakit jantung di seluruh dunia.

Penyakit jantung adalah nama umum untuk keadaan dan gangguan yang menjejaskan

jantung dan saluran darah. Ia boleh menyerang mana-mana orang yang sihat tanpa

petunjuk atau tanda, sama ada muda atau tua. Mereka kurang dapat dilihat dan boleh

disemak secara berterusan. Oleh itu kajian ini membangunkan Sistem Ramalan

Jantung. Sistem ini merupakan sistem sokongan pengguna akhir dan sistem

perundingan dalam talian. Ia membolehkan pengguna mendapat bimbingan segera

mengenai isu-isu jantung mereka dengan menjawab set soal selidik tentang penyakit

jantung. Sistem ini meliputi pelbagai gejala penyakit jantung seperti Angina,

Arrhythmia, Fibrillation Atrium, Cardiomyopathy, kegagalan jantung, dan serangan

jantung. menggunakan teknik perlombongan data. Juga, sistem ini boleh digunakan

sepanjang masa dan di mana sahaja

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CONTENTS

PAGE

DECLARATION ii

CONFIRMATION iii

DEDICATION Iv

ABSTRACT v

ABSTRAK vi

CONTENTS ix

LIST OF TABLES xii

LIST OF FIGURES xvi

LIST OF ABBREVIATIONS xv

CHAPTER I INTRODUCTION

1.1 Background 1

1.2 Problem statement 1

1.3 Objectives 2

1.4 Scopes 2

1.4.1 User Scope 2

1.4.2 Admin Scope 2

1.5 Expected Results 3

1.6 Limitation of Work 3

1.7 Report Organizing 3

CHAPTER II LITERATURE REVIEW

2.1 Introduction 5

2.2

2.3

Heart Disease

Exists System

5

6

viii

2.4

2.5

Statistical Case-Based Reasoning Expert System:

Application to Medical Diagnosis (Park et al.,

2006)

Decision Support System by Using Multilayer

Perception (Godara & Nirmal, 2010)

7

7

2.6 Rule-Based Concept and Theory 8

2.6.1 Rule Based System in general 9

2.7 Chapter Summary 9

CHAPTER III

METHODOLOGY

3.1 Introduction 11

3.2 Spiral Model 11

3.2.1 Requirement Gathering 12

3.2.2 Planning Phase 12

3.2.3 Analysis phase 13

3.2.4 Iteration Phase 13

3.2.5 Testing and Evaluation 14

3.2.6 Deployment Phase 14

3.3 System Design 14

3.3.1 Framework 14

3.3.2 Context Diagram 15

3.4 Data Flow Diagram Level 0 16

3.4.1 Data Flow Diagram Details Level 0 16

3.4.2 Manage Treatment 18

3.4.4 Manage Symptoms & Recommendation 18

3.4.5 View Record 19

3.5 Data Flow Diagram Level 1 19

3.5.1 Update Symptoms 20

3.5.2 Process Add Symptoms 20

3.5.3 Process Delete Symptoms

3.5.4 Process Update Recommendation

(Treatment and Medication)

20

20

ix

3.5.5 Process Add Recommendation

(Treatment and Medication)

3.5.6 Process Delete Recommendation

(Treatment and Medication)

20

20

3.5.6 Process Delete Recommendation

(Treatment and Medication)

20

3.5.7 Process View Symptoms &

Recommendation (Treatment and Medication)

20

3.6 Entity Relationship Model 21

3.7 Database Modelling

3.7.1 Database Design 22

3.7.1.1. Admin Table 22

3.7.1.2 Table Disease 22

3.7.1.3 Table Treatment 22

3.7.1.4 User Table 22

3.7.1.5 User_Test Table 23

3.7.1.6 User_Profile Table 23

CHAPTER IV

IMPLEMENTATION AND TESTING

25

4.1 Introduction 25

4.2 Homepage 25

4.2.1. Registration for User 26

4.2.2 Pop up 26

4.3 4.3 Login 27

4.3.1 List of Symptoms for User 27

4.3.2 Diagnosis 28

4.3.3 Test History 29

4.3.4 Print Report 29

4.3.5 Change password/ update profile 30

4.3.6 Pop up for update 30

4.4 Admin login

4.4.1 Admin Main Page

31

32

x

4.4.2 Successful pop up

4.4.3 Modify Symptoms

32

33

4.4.4 Update symptoms

4.4.5 Successful Update Pop Up

4.4.6 Modify treatment and medication

34

34

4.4.7 Treatment and medication update 35

4.4.8 Successful update pop up 36

4.5 View user 37

4.5.1 Deleting User 37

4.6 Contact 38

4.6.1 Feedback Message 38

4.7 TEST CASE 39

4.7.1 Type of testing 39

4.7.2 Test Case 40

4.7.3 Summary 41

CHAPTER V

CONCLUSION AND LIMITATION

42

5.1 Introduction 42

5.2 Project Contribution 42

5.3 5.3 Future Works 42

5.4 5.4 Project Limitation 43

5.5 Overall Conclusion 43

REFERENCES 44

xi

LIST OF TABLES

TABLE TITLE PAGE

3.1 Admin Table 22

3.2 Table Disease 22

3.3 Table Treatment 23

3.4 User Table 23

3.5 User_Test Table 23

3.6 User_Profile Table 24

4.1 Test Case for User Registration, Login and Log Out 40

4.2 Test Case for Admin Login and log out 41

4.3 Admin Modification Page 41

xii

LIST OF FIGURES

FIGURE TITLE PAGE

3.1 The Spiral Model 12

3.2 The Framework 15

3.3 The Context Diagram 16

3.4 The Data Flow level 0 17

3.5 The Data Flow Level 1 19

3.6 The Enhanced Entity Relationship 21

4.1 Homepage Interface 25

4.2 Registration Section 26

4.3 Pop up message 26

4.4 Login Phase 27

4.5 List of Symptoms for User 27

4.6 Diagnose Phase 28

4.7 History Phase 29

4.8 Print Report 29

4.9 Update Profile 30

4.10 Successful Pop-up Update 31

4.11 Admin Login Phase 31

4.12 Admin Update Page 32

4.13 Successful Pop-up Message 33

4.14 Modify Symptom Phase 33

4.15 Symptoms Update 34

4.16 Pop-up Update 34

4.17 Treatment and Medication Modification 35

4.18 Update Treatment/Medication 36

4.19 Successful Pop-up message update 36

4.20 View User/ Delete Phase 37

4.21 Successful Deleted Pop-up 37

4.22 Contact Phase 38

4.23 Feedback Message 38

xiii

LIST OF ABBREVIATIONS / TERMS / SYMBOLS

CD Context Diagram

DFD Data Flow Diagram

ERD Entity Relationship Diagram

FYP Final year project

xiv

LIST OF APPENDICES

APPENDIX TITLE PAGE

A Ghent Chart 48

1

CHAPTER I

INTRODUCTION

1.1 Background

Heart disease is a general name for a variety of diseases that make the blood vessels to

be at risk. The manifestation of heart disease varies base on the particular types of

such sickness. There is a particular disease that affects the heart structure and

functions known as congenital heart disease as a result of different heart improvement

stage ahead delivery. The heart is meant to be congested when it fails to circulate

adequate blood to the other part of the human physique. There is numerous type of

problems that occur in the heart. That includes a cardiovascular disease that has a

medical term called an ischemic and coronary disease is referred to damage in the

heart that occurs because of a shortage of blood to the heart reduced.

1.2 Problem Statement

Heart disease prediction using data mining is one of the most exciting and challenging

work. The lack of expert and specialists and diagnoses that went high wrongly has

required the demand to develop or create an efficient and fast system for detection.

Without this system, diseases will be diagnosed manually by the doctor, and it will

involve cost and time. This system can identify the probability of the disease based on

the symptoms, then recommend the patients in going to the hospital or get treatment.

2

1.3 Objectives

The objective of a project is defined as the project outcome and how to achieve it. It is

also a supporting act to ensure the goals of the project are accomplished. The

objectives of this system are stated below:

1. To identify the heart disease based on the symptoms count of the patients.

2. To implement rule-based technique algorithm in given the specific symptoms to a

disease

3. To develop a system that can diagnose the patient and tell them the type of diseases

they have for further treatment.

1.4 Scope

The scope is essential to set a boundary on what the system will cover in the system’s

development, such that this will give a transparent platform on what people will

expect from this system when it is established later.

Thus, heart disease Detection Using Rule-Based System is focused on manages the

patient or user who has a heart disease results based on the test. Next, the admin

Expert will give the feedback based on the test or diagnose result. This system will

only interact with two primary users who are Admin and user or patient.

1.4.1 User Scope

i. Register user

ii. Diagnose or test using the rule-based technique

1.4.2 Admin Scope

i. Provide the test result or prediction of possible disease base on symptoms provided

ii. Generate report

3

i. System Login Module

- There is a registration and login access for user and admin to access this system.

ii. Suggestion Module

- The system will give advice and suggestions to the user after they predict disease

and the result are positive.

iii. Domain System

- The result will generate based on the answer from Registered User and analyses it

with the Rule-Based algorithm. i.e. (based on symptoms count)

1.5 Expected Results

This system is expected to give an accurate prediction about the heart disease based on

the symptoms that user have entered or base on the possible chosen symptoms that

have been given. This system also expected to give advice and suggestions to the user

after the prediction of the disease type and allow the user to share their health-related

issues for heart disease.

1.6 Limitation of Work

This system will focus on the prediction of heart disease based on the symptoms

details that have was choosing. This system does not give the decision on how it will

be treated or what so ever, it is just only to predict whether the person has heart

disease or not. The result may not be 100% accurate, but the result from this system

will help the user to quickly take action and alert for the heart disease by seeking

consultant from a doctor or diagnose. Which mean the system does not treat the user

or give medicine.

1.7 Report Organizing

The reports organizing each chapter that have on the report it arranges will refer to the

specific format and it easy for readers to understand the whole of the report. The

report is started with chapter 1 that explains the introduction, problem statement,

objective, and scope limitation of work, expected outcome and project planning. The

4

next chapter 2 explains about the literature review related paper research for the

system development. Then, chapter 3 discussed project methodology and requirement

of software and hardware that guide the system development. Chapter 4 deals with

project design and modelling are the core part of the development process. Lastly,

chapter 4 concludes on the project development.

5

CHAPTER 2

LITERATURE REVIEW

2.1 Introduction

Basically, in this chapter, the study of previous research is done. The associated

journal and articles were analyzed to find out what is the weakness of the previous

research that we can overcome. A research paper related to rule-based has proved to

be a powerful tool for decision-making systems, such as expert and pattern

classification systems. Rule-based has already been used in some medical expert

systems. Heart Disease Prediction System was capable of answering queries that the

conventional decision support systems were not able to. It facilitated the establishment

of vital knowledge, e.g., patterns, relationships amid medical factors connected with

heart disease.

2.2 Heart Disease

Heart disease involves the heart or blood vessels. Heart disease is the second leading

cause of death in the world. We have a different disease which is common. Most

people want to reduce those risk factors. In this case, the factors are:

1. Having diabetes is also a risk for heart disease.

2. Substance abuse such as cocaine

3. Being overweight

4. Smoking

5. High blood pressure increases the risks of and heart failure

6. Excess cholesterol in blood build up inside the walls of heart’s arteries (blood

vessels)

6

The help of people can decrease the disease by taking steps to cube aspect mentioned.

Like checking their blood pressure w the cholesterol level, refraining from smoking

and having enough exercise.

2.3 Exists System

In an existing study experimented on a sample database of patients’ records. The

neural net is tested and trained with 13 input variables such as Age, Blood Pressure,

Angiography’s report and the like. The supervised network has been favored for

diagnosis of heart diseases4. Training was carried out with the aid of backpropagation

algorithm. Whenever feed data that was not known doctor, the system identified the

unknown data from comparisons with the trained data and generated a list of probable

diseases that the patient is liable with. The success rate for imprecise inputs to retrieve

the desired output is closest to 100%.

In another study, the problem of identifying constrained association rules for heart

disease prediction was studied by5. The underlying dataset encompassed medical

records of people having heart disease with attributes for risk factors, heart perfusion

measurements and artery narrowing.

Three constraints were introduced to decrease the number of patterns. First one

necessitates the attributes to appear on only one side of the rule. The second one

segregates attributes into uninteresting groups. The ultimate constraint restricts the

number of attributes in a rule9. Experiments illustrated that the constraints reduced the

number of discovered rules remarkably besides decreasing the running time. Two

groups of rules envisaged the presence or absence of heart disease in four specific

heart arteries.

In 2010 A study was regulated for a prognostic model for the Ischemic Heart Disease

(IHD) The result shows that BPNN and BNN gave the highest classification accuracy

of 78.43 %, while RBF kernel SVM gave the lowest classification accuracy of 60.78

%. BNN presented the best sensitivity of 96.55 %, and RBF kernel SVM displayed the

lowest sensitivity of 41.38 %. Both polynomial kernel SVM and RBF kernel SVM

7

presented the minimum and maximum specificity of 45.45 % and 86.36 %,

respectively.

After reviewing the above pieces of literature, the researcher was motivated to work

on a classification model that is sought to predict heart disease cases based on patterns

generated from International Cardiovascular Hospital database7. This study is

different in two ways from the studies that are presented above; the first one is the

data that is used for this study is collected from transthoracic echocardiography report

of patients and the second one is the classification models are developed on a much

larger dataset. As far as the knowledge of the researcher is concerned this study will

be the first of its kind in Ethiopia that applied data mining to predict heart disease8. In

the medical field, several diagnostic tools for heart disease were developed in different

AI techniques.

2.4 Statistical Case-Based Reasoning Expert System: Application to Medical

Diagnosis (Park et al., 2006)

In the research of those authors, Statistical Case-Based Reasoning (SCBR), this new

knowledge extraction technique suggested in SCBR roles to adopt an optimal number

of neighbors dynamically by considering the distribution of the distances between

cases. It was improved from CBR and SCBR where a selection of the case is based on

the degree of similarity between the potential of neighbors in each other case that was

presented by the authors in this paper. Step one of SCBR was to scale data then learn

the distribution of distances of the database. Then, the authors found out the optimal

cut-off probability threshold by calculation, and the last step is to perform CBR by

selected neighbors and calculate the result.

The database used in this system is the same as the database used in this study. This

system implemented 13 attributes in SCBR to diagnose heart disease and compare the

result with the final attribute (Aha, 1988).

8

2.5 Decision Support System by Using Multilayer Perception (Godara & Nirmal,

2010)

This paper explains the supervised feed-forward neural network and the usage of

backpropagation learning algorithm with momentum term and augmented learning

rate. In this paper, researchers mentioned that data mining had been heavily used in

medical field to include patient diagnosis records to identify the result of the patients.

Multi-layer perception is a branch of a neural network with a supervised learning

algorithm and backpropagation. Researchers also provided the result for comparison

of the accuracy of multi-layer perception and multi-layer perception with digging

approach.

2.6 Rule-Based Concept and Theory

A rule-based system is a set of “if-then” statements that use a set of assertions, to

which are classic example of a rule-based system is the domain-specific expert system

that uses rules to make deductions or choices. For example, an expert system might a

doctor choose the correct diagnosis based on a cluster of symptoms, or select tactical

moves to play a game. In software development, rule-based systems can be used to

create software that will provide an answer to a problem in an expert system. This

type of system may also be called an expert system. Example of Rule-Based Concept:

IF (fever) THEN Malaria

IF (Coldness) THEN Malaria

IF (Throb) THEN Malaria

IF (Sweat) THEN Malaria

IF (Sometimes color of urine is black water fever) THEN Malaria

IF (Headache) THEN Malaria

IF (Vomiting) THEN Malaria

IF (Muscle pain) THEN Malaria

IF (High temperature) THEN Malaria

IF (Diarrhoea) THEN Malaria

IF (Coma (Seizure)) THEN Tuberculosis

IF (Stiff Neck) THEN Tuberculosis

9

IF (Headache) THEN Tuberculosis

IF (Abdominal Pain) THEN Tuberculosis

IF (Weight Pain) THEN Tuberculosis

IF (Fever) THEN Tuberculosis 13

IF (Masses along the neck) THEN Tuberculosis

IF (Draining Sinus) THEN Tuberculosis

IF (Small Reddish brown lesions (face, eyelid, nose, cheek, and ear)) THEN

Tuberculosis

IF (Reddish brown wart-like growth on the body) THEN Tuberculosis

IF (Skin lesions on hand, feet, elbow, and knees) THEN Tuberculosis

IF (Ulcer or abscesses on the Skin) THEN Tuberculosis

IF (Necrosis of infected Skin) THEN Tuberculosis

IF (Stiffness of the affected area) THEN Tuberculosis

IF (Blood present in Urine) THEN Tuberculosis

IF (Painful or uncomfortable Urination) THEN Tuberculosis

IF (Hemoptysis (coughing up blood)) THEN Tuberculosis

2.6.1 Rule Based System in general

Rule-based system is said to be one of the simplest form of artificial intelligence. The

rule based system uses a set of rules as the knowledge representation for knowledge

that is coded into the system. In short, rule-based system tries to mimic the reasoning

of human expert in solving a problem. Rule-based system represent knowledge in a set

of rules that tells the system what to do or what to conclude in different situations

instead of representing knowledge in a declarative, static way as a set of things which

are true.

A rule-based system is a way of encoding a human expert’s knowledge in a Narrow,

specialised domain into an automated system. The system is created by using a Set of

assertions and a set of rules that tells the system how to act on the assertion set. In a

typical ruled-based expert system, a rule consists of several premises.

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Conclusively, if all the premises are true, then the conclusion is considered true. The

components of a ruled based expert system include the knowledge base, inference

engine, knowledge acquisition component, and explanation system.

2.7 Chapter Summary

This chapter discussed the collection of a literature review that had been reviewed

during the feasibility studies. The literature review helps a developer to discover the

problem of previous research or systems which needs to be overcome in this system

development. Besides that, it also can gain an understanding of the system that

undergoes the development process.

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CHAPTER 3

METHODOLOGY

3.1 Introduction

The methodology is the process, step or stages used to collect information and data to

make decisions. The methodology is chosen from the life circle of software

development model. The SDLC that will be used for this project is Iterative and

Incremental Model. In this chapter, it will explain more detail about every phase that

involved with this project development. This model has been selected because project

can be developed through cycle of phase. The development of the project is that it

must follow the phase that is a phase at a time. If there is any correction, it can be

done in the middle of the process. Incremental model included five phases which are

requirement analysis, design, implementation and unit testing, integration and system

testing and operation.

3.2 Spiral Model

Spiral Model is a combination of sequential and prototype model. There are specific

activities that are done in one iteration; which is spiral where the output is the small

prototype of the large software. Thus, the same activities are repeated for all the

spirals until the whole software is built. There are six phases involved in the spiral

12

Figure 3.1 The Spiral Model

3.2.1 Requirement Gathering

Requirement gathering is the first step for this methodology for the project. On this

phase, all requirements are gathered together so that all of the needed requirement can

be stated, analyse and process. All the requirements will be analyse if it is suitable to

develop the system. Also on this phase, all the materials that are required have been

prepared.

i. Hardware

Personal Computer (PC)

ii. Software

a) Google Chrome

b) Notepad ++

c) XAMPP

d) Microsoft Office

e) MySQL server Workbench

3.2.2 Planning Phase

In the planning phase cost of building the system, benefit analysis, risk management

plan and feasibility study are included. It has also included the development of the

project planning such as schedules, Gantt Chart that function to plan, organize the

13

report progress for the system within the system environment and system management

plan. The most important in this phase is to develop an overall model while improving

the initial model before continuing to the next phase, an analysis phase.

3.2.3 Analysis phase

This phase includes the task that goes determining the needs and condition require in

order to build the system and to recognize the stakeholders (user) in building the

system. Analysis of user need and requirement the needs and requirement while

determining the main functionality which include creating a detailed of RSS

functional and non-functional requirement of the system.

Collection of data and information for the system is done in this phase. Data gathering

about information of finding the shortest route, djikstra’s algorithm that will be

applied in this system either from journals, articles, books white or research paper.

SWOT analysis also will be done as an early precaution to recognize the weakness of

the system, thus figuring a way to overcome it. All details gather are grouped into sets

and course areas and being broken down as at ask or model for iteration phase.

3.2.4 Iteration Phase

Every design of iteration will be designed in this phase and being built according to

the iteration as planned. Besides that, at each development of iteration some testing

and validation will be done in order to identify whether each development iteration are

in sync with the guidelines set in an earlier phase (planning phase).

3.2.4.1 Design

The first sketch (rough sketch) of iteration is the main challenge in this phase; it’s also

affecting the future of the whole system. The next iteration it will focus more on the

improvement and adoption of technology that are being used by the software feature in

14

which each iteration requires to produce a good model that give the best result for the end

product.

3.2.4.2 Development

This phase is done after the design phase and after all the design and inspection for

each feature are done successfully with a production of a complete function.

3.2.5 Testing and Evaluation

After the code are successfully being built each of its will be test and evaluate to

ensure that all the development meets the requirement of the software specification on

the compatibility and suitability of the architecture on the technology that has been

designed to be implemented.

3.2.6 Deployment Phase

This phase includes the implementation preparation of the system into the production

environment and resolution of problems identified in the integration. Once the system

passes the acceptance test, documentation for describing task on how to function and

maintain the system in production environment includes post implementation and in

process reviews are done.

3.3 SYSTEM DESIGN

3.3.1 Framework

The figure 3.1 above the framework for the heart Disease Prediction System. The

figure explains how the interaction between system and user occurs. The user will

interact with the user interface and to display results, the system will response and

carries out reasoning whereby the ruled based system provide result.

15

Figure 3.2. The Framework

3.3.2 Context Diagram

From the figure, it is shown that two entities interact with the system which is The

Admin, and the user. The Admin has the ability to interact with the system by logging

in and update charges. The User however can only choose the listed symptoms and

diagnose it for his/her result.

16

Figure 3.3 The Context Diagram

3.4 DATA FLOW DIAGRAM LEVEL 0

The Data Flow Diagram Level (DFD) in Figure 3.3 shown above shows the whole

system flow. There are currently six processes in this system which is registration

Login, Manage user profile, Manage symptoms, Manage treatment medication and

Manage treatment record. Every Process of the system will interact with their related

table or data store in the database in order to complete the Process.

3.4.1 Data Flow Diagram Details Level 0

3.4.1.1. Process 1.0 User Registration & Login

This module allows the user to register and log in into the system to use the system.

The system has one login page for user and admin. This verification will check in

database to verify which homepage it should head on as user. Password and username

for the user entities will be stored in user table.

17

Figure 3.4 The Data Flow level 0

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3.4.1.2 Process 2.0 Manage User Profile

This module allows user to view and update their profile, breakdown of this will be

shown in DFD Level 1.

3.4.1.3 Process 3.0 Answer Test

This module allows user to take the symptoms provide by the system to diagnose the

symptoms selected, to know the perfect disease for the selected symptoms.

3.4.1.4 Process 4.0 View Record And Recommendation

This module allows user to view record of test taken by the user and provide

recommendation after the user take the result is show.

3.4.1.5 Process 5.0 Admin Login

This module allows the admin to log in into the system to use the system. The system

has one login page for user and admin. This verification will check in database to

verify which homepage it should head on as user and admin has different interface.

Password and username for the user entities will be stored in user table.

3.4.1.6 Process 6.0 View User Profile

This module allows the admin to view all the user profile and test results, treatment

and medication of all user.

3.4.2 Manage Treatment

This module allows the admin to view all the treatment. The admin is also allowed to

add new treatment and delete treatment from the system.

19

3.4.4 Manage Symptoms & Recommendation

This module allows the admin to change, delete or add the symptoms and

recommendation (see Figure 3.4).

3.4.5 View Record

This module allows the admin to view the record of diagnosed symptoms taken by the

user (see Figure 3.4).

3.5 Data Flow Diagram Level 1

Data Flow Diagram Level 1 shows the system symptoms update view and controlled

by the admin.

Figure 3.5 The Data Flow Level 1

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3.5.1 Update Symptoms

This module allows admin to update the symptoms. Admin will select which

symptoms to update and update it.

3.5.2 Process Add Symptoms

This module allows admin to add new symptoms in the list of symptoms.

3.5.3 Process Delete Symptoms

This module allows admin choose to remove symptoms from the list. Admin just

select the symptoms from the list and delete it.

3.5.4 Process Update Recommendation (Treatment and Medication)

This module allows admin to update the recommendation.

3.5.5 Process Add Recommendation (Treatment and Medication)

This module allows admin to add new recommendation in the list of recommendation

according to the recommendation prescript by the doctor.

3.5.6 Process Delete Recommendation (Treatment and Medication)

This module allows admin choose to remove recommendation from the list. Admin

just select the recommendation from the list and delete it.

3.5.7 Process View Symptoms & Recommendation (Treatment and Medication)

This module allows admin to view list of symptoms and recommendation

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3.6 Entity Relationship Model

The entity relationship Model illustrates an information system’s entities and the

relationships between those entities; which is clearly described in the entity relationship

diagram (ERD) as shown in Figure 3.5. ERD composed of three things such as identifying

and defining the entities, determine entities‟ interaction and the cardinality of the

relationship. An entity relationship diagram (ERD) illustrates an information system’s

entities and the relationships between those entities. ERD composed of three things such

as identifying and defining the entities, determine entities interaction and the cardinality

of the relationship.

Figure 3.6 The Enhanced Entity Relationship

22

3.7 Database Modelling

The database is important part which is used to store data in systematically

way and can be accessed by authorized user.

3.7.1 Database Design

3.7.1.1. Admin Table

Table 3.1 shows user that contain Admin. The fields are username and password.

Table 3.1 Admin Table

3.7.1.2 Table Disease

Table 3.2 shows user that contain disease. The fields are ID, symptoms, disease and

status.

Table 3.2 Table Disease

3.7.1.3 Table Treatment

Table 3.3 shows user that contain treatment. The fields are ID, disease, treatment,

medication.

23

Table 3.3 Table Treatment

3.7.1.4 User Table

Table 3.4 shows user that contain users. The fields are surname, othername, address,

email, username, and password.

Table 3.4 User Table

3.7.1.5 User_Test Table

Table 3.5 shows user that contain users_test. The fields are ID, username, password,

disease, treatment, medication.

Figure 3.5 User_Test Table

3.7.1.6 User_Profile Table

Table 3.6 shows user that contain user-profile. The fields are Admin, disease,

treatment, users, users_test, users_profile

24

25

CHAPTER 4

IMPLEMENTATION AND TESTING

4.1 Introduction

This project is implemented as a web-based application using hypertext pre-processor

(PHP) language.

4.2. Homepage

Figure 4.1 shows the interface of the homepage for both the Admin and patient/user. It

also shows some information about the heart which includes structure, function,

diseases, risk factors, symptoms and diagnosis of the heart. It will be very advisable

for the user to read before he/she proceed.

Figure 4.1: Homepage Interface

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4.2.1. Registration for User

Figure 4.2 shows the registration for the user before they could login to the system

Figure 4.2: Registration Section

4.2.2 Pop up

Figure 4.3 Pop up message after user have registered that say “successfully”

Figure 4.3: Pop up message

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4.3 Login

Figure 4.4 shows the Login Phase of user login after he/she have registered.

Figure 4.4: Login Phase

4.3.1 List of Symptoms for User

Figure 4.5 shows the interphase after the user login, it will directly go this page where

the user can easily select the symptoms on what he/she is feeling.

Figure 4.5: List of Symptoms for User

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4.3.2 Diagnosis

Figure 4.6 This page show where the user can click diagnose one he/she picks thet

symptoms he/she fells.

Figure 4.6: Diagnose Phase

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4.3.3 Test History

Figure 4.7 this page shows the test result of the user after he/she have diagnose the

symptoms he/she selected. In the test result there is a treatment and medication for

diagnosed symptoms.

Figure 4.7: Test History Phase

4.3.4 Print Report

Figure 4.8 this page shows the report that that can be pretended after the user have

seen his/her test result, then he/she can print the report out.

Figure 4.8: Print Report

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4.3.5 Change password/ update profile

Figure 4.9 shows the page where the user can update his/her profile and where he can

also change his/ her password.

Figure 4.9: Update Profile

4.3.6 Pop up for update

Figure 4.10 shows the successful pop up to the user to if an update is been

successfully done on whatever the user which to update.

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Figure 4.10 Successful Pop-up Update

4.4 Admin login

Figure 4.11 page shows the login page for admin

Figure 4.11 Admin Login Phase

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4.4.1 Admin Main Page

Figure 4.12 shows that the main page for Admin after login, which can update his/her

password. At first the screen will appear to show if the admin wanted to make any

change to his profile, and if any changes were made, admin can click at “Update

button and pop up with massage “Updated successfully” will appear. After update has

been done then he can continue with other processes.

Figure 4.12 Admin Update Page

4.4.2 Successful pop up

Figure 4.13 shows that the admin have updated his/her profile and pop a “successfully

updated” message.

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Figure 4.13: Successful Pop-up Message

4.4.3 Modify Symptoms

Figure 4.14 shows the list of symptoms that can be modified by the Admin.

Figure 4.14: Modify Symptom Phase

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4.4.4 Update symptoms

Figure 4.15 shows the update prosse of the symptoms.

Figure 4.15: Symptoms Update

4.4.5 Successful Update Pop Up

Figure 4.16 shows a pop message after an update have been made on the symptoms

table which includes deletion and insertion.

Figure 4.16: Pop-up Update

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4.4.6 Modify treatment and medication

Figure 4.17 this page shows the list of each disease that can be updated to different

treatment and medication

Figure 4.17: Treatment and Medication Modification

4.4.7 Treatment and medication update

Figure 4.18 shows the process of each modification. This describes how the treatment

and medication is updated

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Figure 4.18: Update Treatment/Medication

4.4.8 Successful update pop up

Figure 4.19 shows the page of pop up message after the update of the treatment and

medication saying “successfully updated’

Figure 4.19: Successful Pop-up message update

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4.5 View user

Figure 4.20 show where the admin can view all the user that have used the system, the

list of all user that login to the system. It shows their surname, other name, username

and password. And it is also possible for the admin to delete any user from the list.

4.20: View User/ Delete Phase

4.5.1 Deleting User

Figure 4.21 this page shows the deletion of a user. And also shows the pop up

message that it has been successfully deleted.

4.21: Successful Deleted Pop-up

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4.6 Contact

Figure 4.22 this page shows the contact form, how the user can contact the admin by

filling the form and sending the admin message through email.

Figure 4.22: Contact Phase

4.6.1 Feedback Message

Figure 4.23 this shows the automatic feedback reply after a message has been sent to

the admin.

Figure 4.23: Feedback Message

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4.7 TEST CASE

A test case is a set of condition under which a tester will determine whether an

application, software system or one of its features is working as it was originally

established for it to do. The process of doing test case can help to find out problems on

the system requirement. In a test case, it consists of component which describes an

input, action or event and an expected response. All of these are used to determine the

application software system is functioning properly. The table below show the test

case for the several process o the system.

4.7.1 Type of testing

There are three type of testing which are unit testing, integration testing and system

testing. The reason why the system is needed to be tested is that to see whether the

system is fully functioning error free and also to meets the user requirement. For unit

testing, it is needed to verify the functionality of the specific code while integration

testing works on expose defect in the interface and the interaction between

components or between the nodules. Moreover, end-to-end testing tests a completely

integrated system to verify so that it will meet its requirement.

4.7.1.1 Black Box Testing

Black box testing is a testing technique in which to test the functionality of the

software without looking at the internal code structure, implementation details and

knowledge of the internal paths of the software. So we can conclude that this type of

testing is just based on the software requirement and specification by just focusing on

the input and output of the software without bothering the knowledge of the software

program.

4.7.1.2 White Box Testing

White box testing will be focusing on strengthening security, improving design and

usability, the flow of input and output through the application. It will test the software

internal structure or work application. It also involves testing a series of predefine

40

input against the desired output so that when a specific input does not come out as the

expected output, you have encountered a bug. This is because the basic objective of

this testing is that to verify its working flow for an application.

4.7.2 Test Case

4.7.2.1 Test Case for User Registration, Login and Log Out

Table 4.1 shows the test case for user registration, login and log out

Table 4.1: Test Case for User Registration, Login and Log Out

Step Test Procedure Expected Result Result

1. Click on “Registration” Link Direct to add form Pass

2. Insert first surname, other

name, address, email, username

and password.

Save into the database and

shows pop-up message

“registration successful”

Pass

3. Insert first surname, other

name, address, email, username

and password, if invalid,

Shows error message pop-

up and return to

registration page

Pass

4. Click on the “login” button

for login

It will go directly to

symptoms page

Pass

5. Select the below “symptoms” to

test your heart

Symptoms selected below Pass

6. Click “diagnose”

Button for result

Show the user result based

on the selected symptoms

Pass

7. Click on profile modification to

update profile

Update your profile

Pop-up message shows

“successfully updated”

Pass

8. Click on the “Log out”

button

Go directly back to the

home page

Pass

41

4.7.2.2 Test Case for Admin Login and log out

Table 4.2 indicates the test case for admin login and log out

Table 4.2: Test Case for Admin Login and log out

Step Action Expected Result Result

1. Click on the “login” button

for login

It will go directly to symptoms

page

Pass

2. Insert username and password It will go to modification page Pass

3. Click on the “Log out” button Go directly back to the home

page

Pass

4.7.2.3 Admin Modification Page

Table 4.3 explains the admin modification page

Table 4.3 Admin Modification Page

Step Action Expected Result Result

1. Click on profile modification

to update profile

Update your profile Pop-up

message shows “successfully

updated”

Pass

2. Click on symptoms

modification to update

symptoms

Update your symptoms Pop-up

message shows “successfully

updated”

Pass

3 Click on disease modification

to update diseases

Update your disease Pop-up

message shows “successfully

updated”

Pass

4.7.3 Summary

In order to use the platform, the registered user must login into the system first while

unregistered user needs to register.

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CHAPTER 5

CONCLUSION AND LIMITATION

5.1 Introduction

This section concludes the documentation of this project in the aspect of planning

designing, implementation and testing.

5.2 Project Contribution

Heart disease prediction system was developed base on objective to assist a patient

with having problems with their heart condition. In this case the users of this system

are patients and admin. The rule-base method is implemented in this system to know

the result of a disease that affects a patient vase on a certain symptoms selected a

result will be shown base on the method. The user will be given some

recommendation after the result have been shown. The user will also be advised to see

a doctor where by a report can be printed to show a doctor for special medication or

treatment and maybe a cross check-up for confirmation. In this case the admin will

know if the prediction right, close or wrong.

5.3 Future Works

One of the key features of these types of analysis is that they have the capability to be

extended or modified based on new datasets. First, by accessing a medical record that

has the patients as separate instances, the system can take into account the co

prevalence of more than two diseases to produce a more complex conditional

probability structure, that itself can be used for more sophisticated graphical models

than naive Bayes or ICI. These predictive powers can be combined using an expert

system that can be trained to weight the distances between diseases in each network

and combine them in one single number representing the similarity. Forth, using

timeline in analysis not only can provide the capacity of modelling the dynamic of

emergence and progression of diseases but also helps to identify whether the

43

comorbidity of two diseases is due to a causal relation between them or just a

correlation resulting from mutual risk factors.

5.4 Project Limitation

The system only allowed the patient to test the disease of the heart at early stage based

on Symptoms and travel area. This system also recommends them to go to the

hospital for a blood test and further treatment if the result from test shows a disease

for a certain user. The patient can also contact the admin for help, query, observation

or recommendation related to the system or their heart issues.

5.5 Overall Conclusion

In this project the problem of constraining and summarizing the algorithms of data

rule-base used in the field of disease and medical prediction are discussed. The focus

is on using the algorithms and combinations of several target attributes for intelligent

and effective heart disease prediction using rule base. For predicting heart disease,

significantly 19 attributes symptoms are listed and with basic rule base technique

other approaches like Association Rule The outcome of predictive rule base technique

on the same symptoms reveals that Decision Tree outperforms and sometime

Bayesian classification is having similar accuracy as of decision tree but other

predictive methods like KNN, Neural Networks, Classification based on clustering are

not performing well. The proposed work can be further enhanced and expanded for

the automation of Heart disease prediction. Real data from Health care organizations

and agencies needs to be collected and all the available techniques will be compared

for the optimum accuracy.

44

REFERENCES

Niti Guru, Anil Dahiya, Navin Rajpal 2007 Decision Support System for Heart

Disease Diagnosis Using Neural Network", Delhi Business Review

Frawley and G. Piatetsky -Shapiro 1996 Knowledge Discovery in Databases: An

Overview. AAAI Press/ The MIT Press, Menlo Park, C.A

Heon Gyu Lee, Ki Yong Noh, Keun Ho Ryu 2007:Mining Biosignal Data: Coronary

Artery Disease Diagnosis using Linear and Nonlinear Features of HRV, LNAI 4819:

Emerging Technologies in Knowledge Discovery and Data Mining pp 56-66

Sharma Purushottam, Dr Kanak Saxena, Richa Sharma” Efficient Heart Disease

Prediction System using Decision Tree” in IEEE International Conference on

Computing Communication and Automation (ICCCA-2015), May 2015.

Sellappan Palaniappan, Ra_ah Awang Intelligent Heart Disease Prediction System

Using Data Mining Techniques", IJCSNS International Journal of Computer Science

and Network Security, Vol.8 No.8

Yanwei, X.; Wang, J.; Zhao, Z.; Gao, Y 1997. Combination data mining models with

new medical data to predict outcome of coronary heart disease. Proceedings

International Conference on Convergence Information Technology

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APPENDICES

APPENDIX A

Ghent Chart

46

ACTIVITY

MONTHS

W

1

W

2

W

3

W

4

W

5

W

6

W

7

W

8

W

9

W

10

W

11

W

12

W

13

W

14 W

15

INITIAL

PLANNING

Idea generation

with SV

Propose a title

project

Draft schedule

PLANNING

Brainstorming on

project

Determine

Problem Statement

Determine

Objective

Determine the

Scope

Write Proposal

Submit Proposal

Analysis And

Design

Analyse existing

system

Elicit requirement

Preparation for

Presentation 1

Presentation 1

Design database

(CD,DFD,ERD)

Proposed Solution

(Methodology)

Proof of concept

Report Correction

Conference of

project

Submit Report

47

48

ACTIVITY

MONTHS

W

1

W

2

W

3

W

4

W

5

W

6

W

7

W

8

W

9

W

10

W

11

W

12

W

13

W

14 W

15

INITIAL PLANNING

Idea generation with

SV

Propose a title project

Draft schedule

PLANNING

Brainstorming on

project

Determine Problem

Statement

Determine Objective

Determine the Scope

Write Proposal

Submit Proposal

ANALYSIS AND

DESIGN

Analyse existing

system

Elicit requirement

Preparation for

Presentation 1

Presentation 1

Design database

(CD,DFD,ERD)

Proposed Solution

(Methodology)

Proof of concept

Report Correction

Conference of project

Submit Report