Presentation 2022-07-09
Development of a prognosis prediction for Covid-19 using deep learning
Yuma Iwao, Naoko Kawata, Yuki Sekiguchi, Hideaki Haneishi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Many studies have been reported on the prediction of COVID-19 severity using deep learning. However, most of them predicted severity based on CT images alone, and there have been few reports that took clinical information into account. We developed a system using deep learning to predict the severity of COVID-19 more accurately by adding clinical information to the image-based network. 385 cases were trained and 112 cases were evaluated.As a result, we confirmed 2-6% improvement in accuracy, sensitivity, and specificity.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Chest CT / COVID-19 / redict the severity / Deep Learning
Paper # MI2022-42
Date of Issue 2022-07-01 (MI)

Conference Information
Committee MI
Conference Date 2022/7/8(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English) Medical imaging, recoginition, etc.
Chair Hidekata Hontani(Nagoya Inst. of Tech.)
Vice Chair Hideaki Haneishi(Chiba Univ.) / Takayuki Kitasaka(Aichi Inst. of Tech.)
Secretary Hideaki Haneishi(Yamaguchi Univ.) / Takayuki Kitasaka(Univ. of Hyogo)
Assistant Takeshi Hara(Gifu Univ.) / Yoshito Otake(NAIST)

Paper Information
Registration To Technical Committee on Medical Imaging
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Development of a prognosis prediction for Covid-19 using deep learning
Sub Title (in English)
Keyword(1) Chest CT
Keyword(2) COVID-19
Keyword(3) redict the severity
Keyword(4) Deep Learning
1st Author's Name Yuma Iwao
1st Author's Affiliation National Institutes for Quantum Science and Technology(QST)
2nd Author's Name Naoko Kawata
2nd Author's Affiliation Chiba University(Chiba Univ)
3rd Author's Name Yuki Sekiguchi
3rd Author's Affiliation Chiba University(Chiba Univ)
4th Author's Name Hideaki Haneishi
4th Author's Affiliation Chiba University(Chiba Univ)
Date 2022-07-09
Paper # MI2022-42
Volume (vol) vol.122
Number (no) MI-98
Page pp.pp.39-41(MI),
#Pages 3
Date of Issue 2022-07-01 (MI)