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Paper Abstract and Keywords
Presentation 2021-01-28 15:40
Consideration about Learning Scheme with Outlier Detection in Training Data for Prediction Model of Medication Effect Using Recurrent Neural Networks
Yoshitomo Sakuma, Takumi Kobayashi, Chika Sugimoto, Ryuji Kohno (Yokohama National Univ.) MICT2020-27 MBE2020-32
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, the application of machine learning to the medical and healthcare field has attracted attention. In particular, assisting general anesthesia during surgery and remote management of insulin administration for diabetic patients are research subjects that are attracting attention as applications of machine learning. In previous research, we have also proposed a method for predicting the dosing effect of anesthetics using a recurrent neural network (RNN), which is one of the methods of machine learning. However, if RNNs are learned using outliers (artifacts) included in vital data due to other vital, prediction accuracy is decreased. Therefore, in this study, we consider an outlier detection method for training data to realize dependable prediction the effect of medication on the human body using RNN.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning / Prediction Model / Neural Network / Outlier Detection / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 348, MICT2020-27, pp. 28-33, Jan. 2021.
Paper # MICT2020-27 
Date of Issue 2021-01-21 (MICT, MBE) 
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 MICT2020-27 MBE2020-32

Conference Information
Committee MBE MICT  
Conference Date 2021-01-28 - 2021-01-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MICT 
Conference Code 2021-01-MBE-MICT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Consideration about Learning Scheme with Outlier Detection in Training Data for Prediction Model of Medication Effect Using Recurrent Neural Networks 
Sub Title (in English)  
Keyword(1) Machine Learning  
Keyword(2) Prediction Model  
Keyword(3) Neural Network  
Keyword(4) Outlier Detection  
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1st Author's Name Yoshitomo Sakuma  
1st Author's Affiliation Yokohama National University (Yokohama National Univ.)
2nd Author's Name Takumi Kobayashi  
2nd Author's Affiliation Yokohama National University (Yokohama National Univ.)
3rd Author's Name Chika Sugimoto  
3rd Author's Affiliation Yokohama National University (Yokohama National Univ.)
4th Author's Name Ryuji Kohno  
4th Author's Affiliation Yokohama National University (Yokohama National Univ.)
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Speaker Author-1 
Date Time 2021-01-28 15:40:00 
Presentation Time 25 minutes 
Registration for MICT 
Paper # MICT2020-27, MBE2020-32 
Volume (vol) vol.120 
Number (no) no.348(MICT), no.349(MBE) 
Page pp.28-33 
#Pages 6 
Date of Issue 2021-01-21 (MICT, MBE) 

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