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Paper Abstract and Keywords
Presentation 2023-01-11 10:50
Comparison of Machine Learning Methods for Decision of Acupoints in Acupuncture and Moxibustion Treatment
Hang Yang (Yamaguchi Univ.), Ren Wu (Yamaguchi Junior College), Mitsuru Nakata, Qi-Wei Ge (Yamaguchi Univ.) MSS2022-54 SS2022-39
Abstract (in Japanese) (See Japanese page) 
(in English) After thousands of years of development, a large number of clinical experiences of acupuncture and moxibustion treatment in traditional Chinese medicine have been recorded in the form of text. Artificial intelligence represented by machine learning can enable computers to learn rules from a large number of existing data through algorithms, train appropriate mathematical models, and use the trained models to analyze and predict the data. This paper aims to train an appropriate model by learning the text data of acupuncture and moxibustion treatment through machine learning algorithms, so as to develop an intelligent system that can master the rules of acupoints and provide more convenient and accurate acupoints prescriptions for treating patients. Specifically, in this paper we build a database of symptoms and acupoints prescriptions, and applying several algorithms to learn the data in the database to train the related mathematical models. As the result of computational experiments, one of the algorithms, Seq2seq with attention, is most effective to provide acupoints prescriptions．
Keyword (in Japanese) (See Japanese page) 
(in English) artificial intelligence / machine learning / acupuncture and moxibustion / traditional Chinese medicine / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 329, MSS2022-54, pp. 54-59, Jan. 2023.
Paper # MSS2022-54 
Date of Issue 2023-01-03 (MSS, SS) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF MSS2022-54 SS2022-39

Conference Information
Committee MSS SS  
Conference Date 2023-01-10 - 2023-01-11 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MSS 
Conference Code 2023-01-MSS-SS 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Comparison of Machine Learning Methods for Decision of Acupoints in Acupuncture and Moxibustion Treatment 
Sub Title (in English)  
Keyword(1) artificial intelligence  
Keyword(2) machine learning  
Keyword(3) acupuncture and moxibustion  
Keyword(4) traditional Chinese medicine  
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1st Author's Name Hang Yang  
1st Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
2nd Author's Name Ren Wu  
2nd Author's Affiliation Yamaguchi Junior College (Yamaguchi Junior College)
3rd Author's Name Mitsuru Nakata  
3rd Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
4th Author's Name Qi-Wei Ge  
4th Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
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Speaker Author-1 
Date Time 2023-01-11 10:50:00 
Presentation Time 25 minutes 
Registration for MSS 
Paper # MSS2022-54, SS2022-39 
Volume (vol) vol.122 
Number (no) no.329(MSS), no.330(SS) 
Page pp.54-59 
#Pages 6 
Date of Issue 2023-01-03 (MSS, SS) 

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