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 |
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SIP2019-14 IE2019-14 MI2019-14 |
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