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Full Project – Design and implementation of a muscleskeletal disorder diagnosis using expert systems

Click here to Get this Complete Project Chapter 1-5

CHAPTER ONE

INTRODUCTION

1.1 BACKGROUND OF THE STUDY

Expert systems are applications of artificial intelligence which are complex systems which emulate decision making ability of a human expert. They solve problems by using the bodies of existing knowledge and make decision using if-then rules of the algorithm.

Expert systems are divided into the

Knowledge base: Which refers to the base facts that are known about the subject matter which in this case are symptoms of muscle skeletal diseases
Inference engine: This is the set of rules then applied to a new case based on the knowledge base. These also include explanation and debugging abilities.

Expert systems were chosen for this project because of its proven method in the field of Artificial Intelligence.

1.2 STATEMENT OF THE PROBLEM

This study wants to solve the problems of slow diagnosis and wrong diagnosis. In an expert system, you get a near accurate result for predictive diagnoses. Slow diagnosis in the sense that in a traditional doctor-patient relationship, you get a fairly longer time to predict what exactly is wrong with the patient. In the new system you get a very fast predication such practitioners can work with. You can also reduce wrong diagnoses in this system in the sense that there are specific symptoms that a re peculiar to certain kinds of muscle skeletal diseases and the knowledge base helps in making the right decisions.

1.3 MOTIVATION OF THE STUDY

The study is motivated by the need for health practitioners to be able to assist patients more effectively and adequately. The knowledge base and the algorithms work in tandem alongside doctors and specialists to make correct descriptions.

1.4 AIMS AND OBJECTIVES OF THE STUDY

The aims and objectives of this system include;

Developing a muscle skeletal disorder diagnosis system.
Studying previous work on the proposed topic and looking for ways to improve them.
Optimizing the system to include an accurate knowledge base and an efficient inference engine.
Implementing security standards with the system.
Creating the system to give accurate diagnoses to guest users.

1.5 OUTLINE OF METHODOLOGY

The implementation of this idea and project was done with the user of the server-side programming language PHP and the MySQL database querying language. These languages were chosen for their server-side compatibility, their high level of security and for the general web compatibility. The front end technologies used include HTML, CSS and JavaScript. This will also be hosted as a web application on an online domain.

1.6 SCOPE OF THE STUDY

The study covers a simple diagnosis specifically an health center that treats musle skeletal diseases which is on a relatively small scale, which can then be scaled up for bigger hospitals and clinics.

1.7 SIGNIFICANCE OF THE STUDY

The study is very significant in studying, analyzing and postulating more efficient and trustworthy ways of making accurate decision on behalf of health practitioners and patients alike through conditional statements built into the system.

1.8 OPERATIONAL DEFINITION OF TERMS

EXPERT SYSTEMS: This refers to an artificial intelligence implemented system that emulates the decision making ability of a human expert. It solves problems using some sort of reasoning through bodies of knowledge that are represented through if-then rules rather than procedural algorithms.
ARTIFICAL INTELLIGENCE: This refers to the intelligence demonstrated by machines using complex algorithms. It generally describes machines that mimic cognitive functions of actions associated with the human mind, such as learning and problem solving.
KNOWLEDGE BASE: This refers to a set of data that has been collected about a particular subject and can be used to make informed decisions
INFERENCE ENGINE: The inference engine is a system that applies logical rules to a knowledge base to deduce new information.

1.9 ORGANISATION OF THE PROJECT

The project is organized such that; Chapter One gives a brief introduction in form of the Background of the Study of a general overview of a muscle skeletal disease diagnosis using Expert Systems. In Chapter Two, we have a broad look at the related implementations of such Expert systems. Chapter Three examines the System Architecture, the system design and analysis. Chapter Four presents the implementation of the project using necessary programming languages and development models. It also presents the result of testing carried out. Chapter Five rounds off the project work with the summary, conclusions and recommendations for future works.

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Full Project – Design and implementation of a muscleskeletal disorder diagnosis using expert systems

Click here to Get The Complete Research Project Chapter 1-5

Full Project – Design and implementation of a muscleskeletal disorder diagnosis using expert systems

CHAPTER ONE

INTRODUCTION

1.1 BACKGROUND OF THE STUDY

1.2 STATEMENT OF THE PROBLEM

1.3 MOTIVATION OF THE STUDY

1.4 AIMS AND OBJECTIVES OF THE STUDY

1.5 OUTLINE OF METHODOLOGY

1.6 SCOPE OF THE STUDY

1.7 SIGNIFICANCE OF THE STUDY

1.8 OPERATIONAL DEFINITION OF TERMS

1.9 ORGANISATION OF THE PROJECT

Full Project – Design and implementation of a muscleskeletal disorder diagnosis using expert systems

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