Title: Assumption of constructing intelligent recommend model of diabetic Chinese patent medicines

Authors: Chaonan Liu; Yuzhou Liu; Enliang Yan; Jianfeng Fang

Addresses: The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong, China ' Shenzhen Bao'an Traditional Chinese Medicine Hospital, Shenzhen 518000, Guangdong, China ' School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, Hebei, China ' The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou 510405, Guangdong, China

Abstract: Responding to the urgent requirements for rational use of diabetic TCM patent medicines, this study comprehensively, objectively and accurately reveals the "treatment-formula-drug-dosage-property" knowledge of Chinese patent medicines on the basis of TCM principles, EBM, clinical practice and partial order theory. It establishes a multi-level, partial-order visualised expression method for TCM treatment in diabetes, and constructs an intelligent recommendation model of diabetic Chinese patent medicines, which provides technological approaches for promoting rational use of Chinese patent medicines. The completed results prove that this method could effectively find out practical guiding knowledge and give reasonable suggestions for drug use.

Keywords: diabetes; Chinese patent medicines; machine learning; knowledge discovery.

DOI: 10.1504/IJCAT.2020.111094

International Journal of Computer Applications in Technology, 2020 Vol.64 No.1, pp.68 - 80

Received: 30 Mar 2020
Accepted: 25 May 2020

Published online: 21 Oct 2020 *

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