Newly developed artificial intelligence algorithm for COVID-19 pneumonia: utility of quantitative CT...
Newly developed artificial intelligence algorithm for COVID-19 pneumonia: utility of quantitative CT texture analysis for prediction of favipiravir treatment effect
About this item
Full title
Author / Creator
Ohno, Yoshiharu , Aoyagi, Kota , Arakita, Kazumasa , Doi, Yohei , Kondo, Masashi , Banno, Sumi , Kasahara, Kei , Ogawa, Taku , Kato, Hideaki , Hase, Ryota , Kashizaki, Fumihiro , Nishi, Koichi , Kamio, Tadashi , Mitamura, Keiko , Ikeda, Nobuhiro , Nakagawa, Atsushi , Fujisawa, Yasuko , Taniguchi, Akira , Ikeda, Hirotaka , Hattori, Hidekazu , Murayama, Kazuhiro and Toyama, Hiroshi
Publisher
Singapore: Springer Nature Singapore
Journal title
Language
English
Formats
Publication information
Publisher
Singapore: Springer Nature Singapore
Subjects
More information
Scope and Contents
Contents
Purpose
Using CT findings from a prospective, randomized, open-label multicenter trial of favipiravir treatment of COVID-19 patients, the purpose of this study was to compare the utility of machine learning (ML)-based algorithm with that of CT-determined disease severity score and time from disease onset to CT (i.e., time until CT) in this setti...
Alternative Titles
Full title
Newly developed artificial intelligence algorithm for COVID-19 pneumonia: utility of quantitative CT texture analysis for prediction of favipiravir treatment effect
Authors, Artists and Contributors
Author / Creator
Aoyagi, Kota
Arakita, Kazumasa
Doi, Yohei
Kondo, Masashi
Banno, Sumi
Kasahara, Kei
Ogawa, Taku
Kato, Hideaki
Hase, Ryota
Kashizaki, Fumihiro
Nishi, Koichi
Kamio, Tadashi
Mitamura, Keiko
Ikeda, Nobuhiro
Nakagawa, Atsushi
Fujisawa, Yasuko
Taniguchi, Akira
Ikeda, Hirotaka
Hattori, Hidekazu
Murayama, Kazuhiro
Toyama, Hiroshi
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8993669
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8993669
Other Identifiers
ISSN
1867-1071
E-ISSN
1867-108X
DOI
10.1007/s11604-022-01270-5
