Diagnosis management system development

Project Abstract

Diagnosis management system development is a crucial area of focus in healthcare technology. This project aims to design and implement a comprehensive system that assists healthcare professionals in accurately diagnosing and managing patient conditions. The system will utilize advanced algorithms to analyze patient data, medical history, symptoms, and test results to generate accurate diagnostic recommendations. The development of the diagnosis management system involves several key steps. Firstly, a user-friendly interface will be designed to input patient information efficiently. This interface will be integrated with databases containing medical knowledge, treatment guidelines, and diagnostic criteria to ensure accurate recommendations. Secondly, machine learning algorithms will be implemented to analyze the input data and generate potential diagnoses based on patterns and similarities with known medical conditions. Furthermore, the system will have the capability to suggest additional tests or procedures to further validate the diagnosis. It will also provide treatment recommendations based on the diagnosed condition, taking into account factors such as patient demographics, comorbidities, and medication allergies. Additionally, the system will have built-in features for monitoring patient progress and adjusting treatment plans as necessary. The diagnosis management system will prioritize accuracy, efficiency, and user-friendliness. Healthcare professionals will be able to access the system from various devices, enabling them to make informed decisions quickly and effectively. The system will also incorporate security measures to ensure the confidentiality and integrity of patient data. Overall, the development of a diagnosis management system holds significant promise for improving healthcare outcomes. By leveraging technology and data analysis, healthcare professionals can enhance their diagnostic accuracy and treatment effectiveness. The system's ability to process vast amounts of medical information and provide evidence-based recommendations will contribute to more personalized and efficient patient care. In conclusion, the diagnosis management system development project aims to revolutionize the way healthcare professionals diagnose and manage patient conditions. By harnessing the power of technology and data analytics, the system will empower healthcare professionals to make informed decisions, ultimately leading to improved patient outcomes and enhanced quality of care.

Project Overview

<p> </p><div><p><strong>INTRODUCTION</strong></p><p><strong>1.0 Introduction</strong></p><p>This chapter presents the introduction to diagnosis management system development. It presents the introduction, theoretical background, statement of the problem, aim and objectives of the study, significance of the study, scope of the study, organization of the research and definition of terms.</p><p>The use of the computer system for collecting and processing medical information is very vital. For instance, detecting diseases at early stage can enable the medical diagnosis officers to overcome and treat them appropriately. Identifying the treatment accurately depends on the method that is used in diagnosing the diseases. A Diagnosis expert system (DExS) can help a great deal in identifying those diseases and describing methods of treatment to be carried out taking into account the user capability in order to deal and interact with expert system easily and clearly. Present expert system uses inference rules and plays an important role that will provide certain methods of diagnosis for treatment.</p><p></p><p>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. An expert system is a system that employs human knowledge captured in a computer to solve problems that ordinarily require human expertise [2]. Expert system seeks and utilizes relevant information from their human users and from available knowledge bases in order to make recommendations [3].</p><p><strong>Diagnosis Information Acquisition</strong>: The data and knowledge of DExS are collected from different sources. The first primary source is the medical knowledge of expert doctors. The second source is from specialized databases, books and a few electronic websites.</p><p><strong>Diagnosis Information Representation:</strong>&nbsp;The proposed system is rule-based system and makes inferences, which require translation of a diseases specific knowledge in the standard symbolic form. In the first phase, the medical background of diseases is recorded through the creation of personal interview with doctors and patients. In the second phase, a set of rules is created where each rule contains in IF part that has the symptoms and in THEN part that has the disease that should be realized. The inference engine (forward reasoning) is a mechanism through which rules are selected to be fired. It is based on a pattern matching algorithm whose main purpose is to associate the facts (input data) with applicable rules from the rule base. Finally, the diseases are produced by the inference engine. This expert system then defines the symptoms for diseases. Diagnosis expert system can be used in consultation since it shows quickly the diagnosis and in addition, it offers explanations of the obtained results, being very helpful to the professional. With the expert system, the user can interact with a computer to solve a certain problem. This can occur because the expert system can store heuristic knowledge.</p><p></p><p>The proposed system performs many functions. It will conclude the diagnosis based on answers of the user to specific question that the system asks the user. The questions provide the system for explanation for the symptoms of the patient that helps the expert system for diagnosis the disease by inference engine. It stores the facts and the conclusion of the inference of the system, and the user, for each case, in database. It processes the database in order to extract rules, which completes the knowledge base</p><p></p></div><div><p><strong>1.1 Statement of the Problem</strong></p><p>The following identified problems necessitated this study:</p><ol><li>Diagnosis is solely based on the physical examination by medical experts.</li><li>Delay in seeing medical experts for diagnosis and prescription.</li><li>Absence of computer based tools to manage medical information of diagnosis.</li></ol><p><strong>1.2 Aim and Objectives of the Study</strong></p><p>The aim of the study is to develop a diagnosis management system with the following objectives:</p><ol><li>To design a system that can aid the registration of diagnosis information to database for future use of diagnosis of patients.</li><li>To implement a system that will facilitate the provision of prescriptions based on disease diagnosed.</li><li>To design a system that can be used to obtain reports of patients’ diagnosis information.</li></ol><p><strong>1.3 Significance of the Study</strong></p><p>The study is significant in the following ways:</p><ol><li>It will provide an avenue to diagnose patients in the case of the absence of medical experts.</li><li>It will reduce the workload of medical experts.</li><li>It will enable easy access to diagnosis information of patients</li><li>The study will be useful to other researchers seeking similar information.</li></ol><p><strong>1.4 Scope of the Study</strong></p><p>This study covers diagnosis management system development, using cottage hospital Ikot Ekpene as a case study. It is limited to the development of a database application that can be used to register medical knowledge of corresponding symptoms, disease and prescription to database for use in diagnosing patients. All data for the study were collected from cottage Hospital, Ikot Ekpene.</p><p><strong>1.5 Organization of the Research</strong></p><p>This research work is organized into five chapters. Chapter one is concerned with the introduction of the research study and it presents the preliminaries, theoretical background, statement of the problem, aim and objectives of the study, significance of the study, scope of the study, organization of the research and definition of terms.</p><p>Chapter two focuses on the literature review. The contributions of other scholars on the subject matter are discussed.</p><p></p><p>Chapter three is concerned with the system analysis and design. It presents the research methodology used in the development of the system. It analyzes the present system to identify the problems and provides information on the advantages and disadvantages of the proposed system. The system design is also presented in this chapter.</p><p>Chapter four presents the system implementation and documentation, the system design, choice of programming language, analysis of modules, programming environment and system implementation.</p><p>Chapter five focuses on the summary, constraints of the study, conclusion and recommendations which are provided in this chapter based on the study carried out.</p><p><strong>1.6 &nbsp;Definition of Terms</strong></p><p><strong>Artificial Intelligence</strong>: The branch of computer science dealing with the mimicking of human-level intelligence in computer programs they are also known as expert systems.</p><p><strong>Diagnosis</strong>: The identification of the nature and cause of illness</p><p><strong>Prescription:</strong>&nbsp;A written order, as by physician, for the administration of a medicine or other intervention</p><p><strong>Patient:</strong>&nbsp; A person who receives treatment from a doctor or medically educated person.</p><p><strong>Therapy:</strong>&nbsp;Treatment of disease or disability</p></div> <br><p></p>