Knowledge-Based Expert System for Medical Disease Diagnosis

Knowledge-Based Expert System for Medical Disease Diagnosis

Abstract

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Healthcare systems are important in improving the quality of life and social welfare in society. Advancement in technology is the driving force behind the improvement of the healthcare sector. Different healthcare technologies like computer-based systems, expert systems, and applications assist health sectors in providing efficient and satisfying services to patients.

The use of expert systems has become popular in today’s generation. Expert systems are computer program which performs complex data processing similar to the evaluation made by a human expert. Expert systems are an efficient alternative for it can conclude and make decisions based on the knowledge, the database of the system.

The researchers gather data about the current methods used by health physicians and doctors in diagnosing a patient’s health status. After a thorough investigation, the researchers have found out that pre-existing medical software is inadequate to fully assist physicians and doctors in diagnosing patients in a time-efficient and accurate manner. Without having an efficient system for diagnosis, health professionals can only diagnose limited numbers of patients.

The researchers of the study aim to design and develop a knowledge-based expert system that can be of great help in the medical field. The researchers proposed the capstone project, entitled “Knowledge-Based Expert System for Medical Disease Diagnosis”. The proposed system is designed to serve as an alternative to diagnose patient’s health problems by inputting the symptoms into the system. The expert system will make clinical reasoning to conclude the diagnosis of the medical disease of the patients. The diagnosis is based on the knowledge about medical diseases in the database of the system.

The implementation of the system will improve the health care provided to patients. The development of the system will make medical disease diagnosis fast and efficient while ensuring an accurate and reliable diagnose result. The implementation of the system will benefit patients who want to increase health awareness by performing medical disease diagnosis for early disease detection.

Knowledge-Based Expert System for Medical Disease Diagnosis
Knowledge-Based Expert System for Medical Disease Diagnosis

Introduction

The capstone project, “Knowledge-Based Expert System for Medical Disease Diagnosis” seamlessly streamlines the process of diagnosing patients to detect early medical diseases. The diagnosis is based on the knowledge about medical diseases in the database of the system. The expert system will conclude and make a diagnosis upon receiving the inputted data about the patient’s health.

Health diagnoses are important for early disease detection. Patients visit physicians or doctors to help them diagnose their health status. The pre-existing medical software is inadequate to fully assist physicians and doctors in diagnosing patients in a time-efficient and accurate manner. Without having an efficient system for diagnosis, health professionals can only diagnose limited numbers of patients. There is an intensified need to fully optimize the diagnostic capabilities of hospitals and healthcare centers.

Proposed Solution

To address the aforementioned needs of the healthcare sector, the researchers proposed the development of the Knowledge-based Expert System for Medical Disease Diagnosis. The system will electronically aid the process of diagnosing a patient’s health status. It will make clinical reasoning to conclude the medical disease diagnosis of the patients. The expert system will diagnose medical diseases based on the inputted health information of the patients. The system will improve the health care provided to patients. The development of the system will make medical disease diagnosis fast and efficient while ensuring an accurate and reliable diagnose result.

Online Expert System with Knowledge Based for Health Clinics Conceptual Framework
Online Expert System with Knowledge Based for Health Clinics Conceptual Framework

Objectives of the Study

General Objective – The general objective of the researchers is to design, develop and implement a knowledge-based expert system for medical disease diagnosis to serve as an alternative in diagnosing a patient’s health status.

The following are the specific objectives of the study:

  1. To electronically transform diagnostic processes in hospitals and healthcare centers.
  2. To automate the process of making clinical reasoning to diagnose patients.
  3. To diagnose a patient’s health status based on knowledge about medical disease stored in a database.
  4. To design a system that only requires inputting a patient’s health information to make a diagnosis.
  5. To make diagnostic processes fast and efficient.
  6. To generate accurate and reliable medical disease diagnosis.
  7. To evaluate the system in terms of user acceptability, effectiveness, quality, timeliness, and productivity.

Scope of the Study

This paper only covers the development process of the Knowledge-based Expert System for Medical Disease Diagnosis. The expert’s system only performs diagnosis that detects medical diseases of patients. The system would require the health information of the patients to be entered into the system to draw a conclusion and diagnose patients. Health physicians, doctors, and patients will serve as respondents to the study.

Significance of the Study

The following individuals or groups will benefit from the success of the project:

Doctors/Physicians. The system will improve their efficiency in diagnosing patients. The system will lessen their workloads for it will act as their alternative in diagnosing the health status of their patients.

Patients. The system will help them receive a fast and efficient diagnostic process. Rest assured that they can receive accurate and reliable diagnostic results.

Researchers. The researchers will gain experience in doing the project with the team and will also harness their knowledge and skills as developers.

Future Researchers. The study will serve as their basis in making their version of the project.

Conclusion

Different healthcare technologies like computer-based systems, expert systems, and applications assist health sectors in providing efficient and satisfying services to patients. The use of expert systems has become popular in today’s generation. With this, the researchers developed a knowledge-based Expert System for Medical Disease Diagnosis. The result of the study showed that the intended users and respondents of the study rated the system satisfactorily. The majority of the target users and respondents are satisfied with the system in terms of user acceptability, effectiveness, quality, timeliness, and productivity.

Hence, the researchers concluded that a Knowledge-based expert system is a good alternative to diagnose a patient’s health condition in a fast and efficient manner. The developed system will improve the health care provided to patients. The system will highly benefit patients who want to increase health awareness by performing medical disease diagnosis for early disease detection. The expert system will increase health awareness and improve quality of life.

Recommendations

The significant result of the study prompted the researchers to highly recommend the implementation of the Knowledge-based Expert System for Medical Disease Diagnosis. The developed system is strongly recommended for its efficiency and reliability that can be rendered to target end-users. The researchers stress the importance of having enough knowledge on how to properly use the system.

The researchers specifically recommend the following:

  1. The health care sector is recommended to adopt the use of an expert system to advance their diagnostic processes.
  2. The researchers recommend that health professionals install the system to serve as their electronic aid in diagnosing their patients.
  3. The system is highly recommended for it’ll make the diagnostic process fast and efficient.
  4. The system is highly recommended for it will generate a highly accurate and reliable diagnostic result.

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