Using expert systems in the medical field has been practiced continuously for the past decades. Many expert systems are being used today for diabetes diagnosis. In this research, we go further by introducing a dynamic expert system that not only diagnoses diabetes but also recommends the right medication depending on the location where the patient lives, on the symptoms of the patient, and on other effective features. This system can be very helpful to many diabetic patients, especially to those who live in rural areas. The knowledge engineer must first consult local pharmacists for available diabetes medications and feeds those brand names into the system's database. Then, once a user enters the symptoms of the patient, the system in return outputs a list of locally available brand names of medications that suit the diabetes type of the patient and that do not pose any danger to his/her health according to the symptoms, effective factors, and results of the patients’ medical tests. This 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, several medical experts and a pharmacist were consulted.

Mohammed Almulla is a professor of computer science at Kuwait University. He has completed his PhD at the age of 33 from McGill University, Montreal Canada. He was the vice president of Kuwait University for academic support services. He has many publications that have been cited over 990 times, and his publication h-index is 17. He has been serving as an editorial board member of several reputed journals.