Optimization of GERD Therapeutic Regimen Based on ANN and Realization of MATLAB

ABSTRACT: Objective To optimize therapeutic regimens for gastro-esophageal reflux disease (GERD), artificial neural networks (ANNs) are used to simulate and set up an intelligent traditional Chinese medicine (TCM) treatment system.Methods ANNs were employed for machine learning; the clinical syndrom...

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Bibliographic Details
Main Authors: Wei-Wu Wang, Rui-Qing Ni, Fang-Yan Yu, Guo-Feng Lou, Cai-Dan Zhao
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2018-03-01
Series:Digital Chinese Medicine
Online Access:http://www.sciencedirect.com/science/article/pii/S2589377719300072
Description
Summary:ABSTRACT: Objective To optimize therapeutic regimens for gastro-esophageal reflux disease (GERD), artificial neural networks (ANNs) are used to simulate and set up an intelligent traditional Chinese medicine (TCM) treatment system.Methods ANNs were employed for machine learning; the clinical syndrome differentiation and treatment determination were simulated through systematic learning of therapeutic regimens for GERD symptoms in the ancient literature; and case simulation was conducted to achieve objective verification.Results The conformity of machinery prescription with the ancient literature exceeded 95%.Conclusion The application of machine learning to TCM intelligent prescription is feasible and worthy of further study. Keywords: Artificial intelligence, TCM expert system, Gastro-esophageal reflux disease, Artificial neural network, MATLAB
ISSN:2589-3777