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

Zainab T. Al-Ars, Abbass Al-Bakry

Abstract


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.

Keywords


AI; communication; expert system; fuzzy logic; K-Mean clustering;

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DOI: http://dx.doi.org/10.12928/telkomnika.v17i6.12715

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TELKOMNIKA Telecommunication, Computing, Electronics and Control
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