A web/mobile decision support system to improve medical diagnosis using a combination of K-Mean and fuzzy logic

Zainab T. Al-Ars (University of Baghdad)
Abbass Al-Bakry (University of Information Technology and Communications Baghdad)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 17, No 6: December 2019

This research provides a system that integrates the work of data mining and expert system for different tasks in the process of medical diagnosis, and provides detailed steps to the process of reaching a diagnosis based on the described symptoms and mapping them with existing diagnosis available on the web or on a cloud of medical knowledge based, aggregate these data in a fuzzy manner and produce a satisfactory diagnosis of the persisting problem. The mobile phone interface would make the system user-friendly and provides mobility and accessibility to the user, while posting updates and reading in details the steps that led to the decision or diagnosis that is reached by the K-mean and the fuzzy logic inference engine. The achieved results indicate a promising diagnosis performance of the system as it achieved 90% accuracy and 92.9% F-Score.