Treatment of Diabetes Type II Using Genetic Algorithm

Majdoleen Al Switi, Bahaaldeen Alshraideh, Abedalrhman Alshraideh, Abudalla Massad, Mohammad Alshraideh


Chronic diseases is an important research field because of the growth of the number of affected people around the world. When someone has diabetes, the body either does not make enough insulin or cannot use its own insulin as well as it should. This causes sugar to build up in blood leading to complications like heart disease, stroke, and neuropathy. Poor circulation leading to loss of limbs, blindness, kidney failure, nerve damage, and death. Diagnosis plays vital role in diabetes treatment otherwise it leads to long term complications in terms of costs of the treatment of the patients and leads to many risks over the patient himself as mentioned above. In this research we propose new methodology to extract the best testing sequence evaluation mechanism for helping doctors to evaluate their patient’s cases and make the best decisions about the medicine being given. We managed to create chromosomes population each of which consists of binary decision tree, as this implementation considered being the best scenario of our problem. The system proves its efficiency by applying it on 50 patients and the results shows accuracy percentage of 95.4%.


clinical decision support system, Genetic algorithms, Diabetes Management.

Full Text:


International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
Creative Commons License
Scopus logo Clarivate Analyatics ESCI logo IET Inspec logo DOAJ logo DBLP logo EBSCO logo Ulrich's logo Google Scholar logo MAS logo