ABSTRACT

CHAPTER ONE

INTRODUCTION

1.1     Background of the Study

During recent years there have been great advances in the field of Biomedicine. The incorporation of computational and artificial intelligence techniques to the field of medicine has yielded remarkable progress in predicting and detecting diseases (Shortliffe et al, 2006).

Artificial Intelligence is seen as the brainpower exhibited by an artificial unit. It is a division of computer science dealing with sharp behavior, knowledge. Research in artificial intelligence is anxious with producing machines to computerize jobs requiring sharp actions. Examples include capability to answer diagnostic and user question, speech and facial recognition (Eugena et al, 2009). Artificial intelligence is separated into two categories. These two categories are conventional artificial intelligence and computational intelligence. Conventional artificial intelligence includes machine learning and statistical analysis. Computational intelligence includes neural networks and fuzzy systems. The other applications of artificial intelligence are automation, computer vision, artificial creativity, expert system and knowledge management (Jimmy, 2013).

Expert System is one of the most common applications of artificial intelligence. It is a computer program that simulates the decision and actions of a person or an association that has specialist facts and experience in a particular field. Normally, such a system contains a knowledge base containing accumulated experience and a set of rules for applying the knowledge base to each particular situation. The major features of expert system are user interface, data representation, inference, explanations etc. Advantages of expert system are increased reliability, reduced errors, reduced cost, multiple expertise, intelligent database, reduced danger etc. Disadvantages of expert system are absence of common sense and no change with changing environment (Mohammed et al, 2011).

Computer-based methods are increasingly used to improve the quality of medical services. Artificial Intelligence (AI) is the area of computer science focusing on creating expert machines that can engage on behaviors that humans consider intelligent (Russell et al, 2002). An expert system is a system that employs human knowledge captured in a computer to solve problems that ordinarily require human expertise. Expert system seeks and utilizes relevant information from their human users and from available knowledge bases in order to make recommendations (Santosh et al, 2010).

Diagnosis system is a system which can diagnose diseases through checking out the symptoms. Knowledge based online diagnosis system is developed for diagnosis of diseases based on the knowledge given by doctors in the system. A computer Program Capable of performing at a human-expert level in a narrow problem domain area is called an expert system. Management of uncertainty is an intrinsically important issue in the design of expert systems because much of the information in the knowledge base of a typical expert system is imprecise, incomplete or not totally reliable (Negnevitsky, 2005).

An expert system (ES) is a kind of information system and acts as a human expert for users by using knowledge base rules in the specific area. The ES consists of the knowledge base and a software module that has an inference engine for decision support to end users in the form of advice. To analyze large volumes of data, data mining that integrates techniques such as artificial intelligence, machine learning, statistics, database systems, and pattern recognition is used. There are a great number of data-mining algorithms for deferent data analysis tasks. Expert systems are used successfully in the medical diagnosis field. The knowledge base of medical expert systems consists of medical information, rule-extracted patient symptoms, and advice for the diagnosis of the patient's diseases. Successful implementations of the artificial neural network (NN)-fuzzy integrated approach in medicine have been reported for diagnosis, treatment, and prediction (Shu-Hsien, 2005).

1.2     Statement of the Problem

The health of individuals is said to be very important. Currently in hospitals, doctors may have to see many patients in other to determine their health problems. This is time consuming and may cause so much stress on the doctor hence medical decision making becomes a very hard activity because the human experts who have to make decisions can hardly process the huge amounts of data. Eventually, treating patients become extremely difficult if the diagnosis method is not good.

Also, most individuals are so busy that they lack the time to visit hospitals when there is a symptom of illness in their body hence coursing body break down or sometimes may even lead to death.

1.3     Aim and Objectives of the Study

The aim of this research work is to design and implement an electronic diagnosis system that will be able to diagnose malaria patients in other to ease the stress of doctors and patients in hospitals.

The objectives are as outlined below:

1. To identify Malaria fever which could be diagnosed using expert system
2. To save time and effort of patients by replacing the traditional malaria diagnosis system through an expert system
3. To assist patients in diagnosing their urination problems before visiting physicians
4. To ease doctors the stress of diagnosing so many patients

1.4     Significance of the Study

This study will serve as a relief to those who are too busy or feel too lazy visiting hospitals since there will be a system that can technically replace doctors in the area of diagnosis.

Also, this study may aid in decreasing the percentage of individuals that fall seriously sick within a particular period due to the fact that they remain unaware of their illness symptoms, and might even decrease the death rate of individuals caused by malaria fever within the system implementation period.

1.5     Scope of the Study

This research work covers the design and implementation of an electronic diagnosis system with special focus to malaria fever as the illness to be diagnosed. The system will only be able to diagnose malaria symptoms in other to determine whether a patient has malaria fever or not.

1.6     Definition of Terms

• Artificial Intelligence: The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
• Expert System: This is a computer program that is designed to emulate and mimic human intelligence, skills or behavior.
• Diagnosis: This is the identification of the nature of an illness or other problem by examination of the symptoms.
• Symptom: This is a physical or mental feature which is regarded as indicating a condition of disease, particularly such a feature that is apparent to the patient.
• Patient: This is a person receiving or registered to receive medical treatment.
• Hospital: This is an institution providing medical and surgical treatment and nursing care for sick or injured people.
• Doctor: This is a person who is qualified to diagnose and treat ill people.