Title: Intelligent home disease pre-diagnosis system for Korean traditional medicine using neural networks

Authors: Kwang Baek Kim; Hyun Jun Park; Doo Heon Song

Addresses: Department of Computer Engineering, Silla University, Gwaebeop-dong, Sasang-gu, Busan 617-736, Korea ' Department of Computer Engineering, Pusan National University, Jangjeon 2-dong, Geumjeong-gu, Busan 609-735, Korea ' Department of Computer Games, Yong-In Songdam College, Mapyeong-dong, Cheoin-gu, Yongin 449-040, Korea

Abstract: In this paper, we propose an intelligent self-health pre-diagnosis system for Korea traditional medicine (KTM). KTM is popularly used among general public with western medicine among Korean people worldwide. Our system consists of the standardised database constructed based on famous textbooks and government reports, fuzzy ART learning engine to extract top three most probable disease from user symptoms and a remote consultation communication platform. The database contents are verified by TM doctors for reliability and the experiment verifies its functionality successfully. We expect this effort can improve the accessibility of healthcare among elderly people and people living in small towns where western type healthcare is not well equipped from community healthcare point of view.

Keywords: intelligent diagnosis; home diagnosis; disease pre-diagnosis; Korean traditional medicine; neural networks; South Korea; KTM; user symptoms; self-pre-diagnosis; fuzzy ART; Korea; self-diagnosis; remote consultation; healthcare accessibility; healthcare technology; elderly people; small towns; community healthcare; healthcare services.

DOI: 10.1504/IJICT.2016.073634

International Journal of Information and Communication Technology, 2016 Vol.8 No.1, pp.1 - 9

Received: 02 Dec 2013
Accepted: 17 Jan 2014
Published online: 15 Dec 2015 *

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