Open AccessLocation-based expert system for diabetes diagnosis and medication recommendation
Author(s) -
Mohammed Almulla
Publication year - 2020
Publication title -
maǧallaẗ al-kuwayt li-l-ʿulūm
Language(s) - English
Resource type - Journals
eISSN - 2307-4116
pISSN - 2307-4108
DOI - 10.48129/kjs.v48i1.8687
Subject(s) - expert system , forward chaining , medical diagnosis , pharmacist , chaining , knowledge base , backward chaining , medicine , medical emergency , family medicine , computer science , medical education , pharmacy , inference engine , psychology , artificial intelligence , pathology , psychotherapist
Using expert systems in the medical field has been practiced continuously for the past decades. There are attempts of using expert systems for a diabetes diagnosis. In this paper, we go further by proposing an expert system that not only diagnoses diabetes but also recommends the right medication depending on the location where the patient lives and on the symptoms of the patient and other effective factors. This system can be very helpful to many diabetic patients, especially to those who are not aware of their disease type or how to control it. The system outputs a list of names of locally available brand names of medications that suit the diabetes type of the patient and that do not pose any danger to the health of the patients according to their symptoms, effective factors, and results of the patients’ medical tests. Our expert system is capable of reasoning using either forward chaining or backward chaining. The rules in the knowledge base are collected from several medical textbooks and articles published in scientific journals, periodicals, and international conferences. To verify the content of the knowledge base, a medical expert and a pharmacist working in Kuwait were consulted.