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Paper Abstract and Keywords
Presentation 2019-05-24 14:50
Fetal state estimation based on Cardiotocogram classification
Shota Harada, Hideaki Hayashi (Kyushu Univ.), Shunsuke Koga (Kyushu Medical Center), Daisuke Shigemi (Obex), Aayako Shibata (Yodogawa Christian Hospital), Masayoshi Yoshida (Hakataminami building Naika Clinic), Yasuyuki Hasuo (Kyushu Medical Center), Seiichi Uchida (Kyushu Univ.) SIP2019-14 IE2019-14 MI2019-14
Abstract (in Japanese) (See Japanese page) 
(in English) Cardiotocogram (CTG) is a recording of fetal heart rate and uterine contraction pressure over time, and is used clinically to determine non-reassuring fetal status.
Estimation of fetal state by CTG is done by visual interpretation. Moreover, it is also reported that the fetal state estimation by CTG has high false positive rate. Therefore, it is desirable to devise an algorithm that can estimate the fetal state from CTG with high accuracy. In this paper, CTG classification is performed using Apgar score as a class label for the purpose of clarifying features useful for CTG classification. In this experiment, we use a highly interpretable classifier to work on CTG classification, and clarify useful features for CTG classification.
Keyword (in Japanese) (See Japanese page) 
(in English) Cardiotocogram / fetal state estimation / apgar score / classification / feature selection / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 51, MI2019-14, pp. 61-63, May 2019.
Paper # MI2019-14 
Date of Issue 2019-05-16 (SIP, IE, MI) 
ISSN Print edition: ISSN 0913-5685    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 SIP2019-14 IE2019-14 MI2019-14

Conference Information
Committee SIP MI IE  
Conference Date 2019-05-23 - 2019-05-24 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MI 
Conference Code 2019-05-SIP-MI-IE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Fetal state estimation based on Cardiotocogram classification 
Sub Title (in English)  
Keyword(1) Cardiotocogram  
Keyword(2) fetal state estimation  
Keyword(3) apgar score  
Keyword(4) classification  
Keyword(5) feature selection  
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1st Author's Name Shota Harada  
1st Author's Affiliation Kyushu University (Kyushu Univ.)
2nd Author's Name Hideaki Hayashi  
2nd Author's Affiliation Kyushu University (Kyushu Univ.)
3rd Author's Name Shunsuke Koga  
3rd Author's Affiliation Kyushu Medical Center (Kyushu Medical Center)
4th Author's Name Daisuke Shigemi  
4th Author's Affiliation Obex Corporation (Obex)
5th Author's Name Aayako Shibata  
5th Author's Affiliation Yodogawa Christian Hospital (Yodogawa Christian Hospital)
6th Author's Name Masayoshi Yoshida  
6th Author's Affiliation Hakataminami building Naika Clinic (Hakataminami building Naika Clinic)
7th Author's Name Yasuyuki Hasuo  
7th Author's Affiliation Kyushu Medical Center (Kyushu Medical Center)
8th Author's Name Seiichi Uchida  
8th Author's Affiliation Kyushu University (Kyushu Univ.)
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Speaker Author-1 
Date Time 2019-05-24 14:50:00 
Presentation Time 25 minutes 
Registration for MI 
Paper # SIP2019-14, IE2019-14, MI2019-14 
Volume (vol) vol.119 
Number (no) no.49(SIP), no.50(IE), no.51(MI) 
Page pp.61-63 
#Pages 3 
Date of Issue 2019-05-16 (SIP, IE, MI) 

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