Presentation 2021-07-02
Extract feature of electro-cardiogram
Naoya Tanaka, Akihiro Fujii, Hiroyasu Shimizu,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Hear diseases has risk of sudden death.The diagnosis of the diseases is usually performed by visual identification from the electrocardiogram data.In this study, we extract waveforms from electrocardiogram data, then the characteristic of the form is classified by machine learning scheme.Risk evaluation is done automatically based on this classifications. We have proposed several machine learning algorithms in terms of risk assessments and compared them to find out optimal methodology for the data set.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) ECG / deep learnig / automated diagnosis
Paper # NLC2021-1
Date of Issue 2021-06-25 (NLC)

Conference Information
Committee NLC / IPSJ-ICS
Conference Date 2021/7/2(1days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Application of natural language processing and intelligent systems, and general topic of NLP
Chair Kazutaka Shimada(Kyushu Inst. of Tech.)
Vice Chair Mitsuo Yoshida(Toyohashi Univ. of Tech.) / Takeshi Kobayakawa(NHK)
Secretary Mitsuo Yoshida(Univ. of Tokyo) / Takeshi Kobayakawa(Hiroshima Univ. of Economics)
Assistant Kanjin Takahashi(Sansan) / Ko Mitsuda(NTT)

Paper Information
Registration To Technical Committee on Natural Language Understanding and Models of Communication / Special Interest Group on Intelligence and Complex Systems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Extract feature of electro-cardiogram
Sub Title (in English)
Keyword(1) ECG
Keyword(2) deep learnig
Keyword(3) automated diagnosis
1st Author's Name Naoya Tanaka
1st Author's Affiliation *(*)
2nd Author's Name Akihiro Fujii
2nd Author's Affiliation Hosei University(Hosei Univ.)
3rd Author's Name Hiroyasu Shimizu
3rd Author's Affiliation *(*)
Date 2021-07-02
Paper # NLC2021-1
Volume (vol) vol.121
Number (no) NLC-82
Page pp.pp.1-6(NLC),
#Pages 6
Date of Issue 2021-06-25 (NLC)