Title: Fuzzy prediction and early detection of stomach diseases by means of combined iteration fuzzy models
Authors: Riad Taha Al-Kasasbeh; Nikolay Korenevskiy; Mahdi Salman Alshamasin; Florin Ionescu; Elena Boitсova; Etab Al-Kasasbeh
Addresses: Department of Electrical Engineering, Faculty of Engineering Technology, Al-Balqa Applied University, Amman 11937, P.O. Box 541324, Jordan ' South West State University, 305040, St. 50 let Oktyabrya, 94, Kursk, Russia ' Department of Mechatronics, Faculty of Engineering Technology, Al-Balqa Applied University, Amman, Jordan ' Steinbeise Transfer Institute Dynamic System, Steinbeise University Berlin, Konstance, Germany ' South West State University, 305040, St. 50 let Oktyabrya, 94, Kursk, Russia ' Al Karak College, Al-Balqa Applied University, Karak, Jordan
Abstract: The work discusses aspects of decision rule synthesis for prediction and early diagnostics of stomach diseases. The distinguishing feature of heterogeneous fuzzy rules of decision making is the fact that they use information about the energetic condition of biologically active points and also features traditionally used in medical practice such as alcohol consumption, smoking tobacco, inheritance, etc. Use of different types of the original data allows us to provide diagnostic efficiency in decisions at the level 0.9 or greater, which makes it possible to recommend the research outcome for medical practice.
Keywords: stomach diseases; fuzzy logic; biologically active points; membership functions.
International Journal of Biomedical Engineering and Technology, 2019 Vol.30 No.3, pp.228 - 254
Received: 24 May 2016
Accepted: 28 Nov 2016
Published online: 28 Jun 2019 *