Title: Developing a biotech scheme using fuzzy logic model to predict occurrence of diseases using person's functional state

Authors: Riad Taha Al-Kasasbeh; Nikolay A. Korenevskiy; Altyn Amanzholovna Aikeyeva; Sofia Nikolaevna Rodionova; Ashraf Adel Shaqadan; Ilyash Maksim

Addresses: Faculty of Engineering Technology, Al-Balqa Applied University, Amman, Salt, Jordan ' South-West State University, Kursk 305040, Russia ' Karaganda State Industrial University, 101400 Respubliki ave, Temirtau, Karagandy, Kazakhstan ' South-West State University, Kursk 305040, Russia ' Zarqa University, Amman, Zarqa, Jordan ' ITMO University - University of Information Technologies, Mechanics and Optics, Saint Petersburg, Russia

Abstract: This research focuses on the evaluation of risk of cardiovascular diseases in persons at various functional states using monitoring stress indicators and developing fuzzy logic model. The model classifies responses in four classes. The physical records of 400 workers were analysed (100 persons for each of four classes). Risk of cardiovascular disease is evaluated using two groups of several characteristics: (1) the subjective test questionnaires and indicators describing the human attention, (2) the level of the functional state can be used as indicator in forecasting and diagnosis, which can be measured by psychological tests to determine the state of human attention. The accuracy of prediction and early detection of cardiovascular and nervous system diseases were estimated in a similar way and it was found out that the use of indicators characterising a person's functional state system improves the quality of classification for these diseases by 10 ± 2% for prediction and diagnostic decision rules.

Keywords: fuzzy logic; classification; functional state; confidence in decision-making; membership function.

DOI: 10.1504/IJCAT.2020.106570

International Journal of Computer Applications in Technology, 2020 Vol.62 No.3, pp.257 - 267

Received: 22 Sep 2018
Accepted: 05 Jun 2019
Published online: 15 Apr 2020 *

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