Age prediction from coronary angiography using a deep neural network: Age as a potential label to extract prognosis-related imaging features | Zendy

Shinnosuke Sawano | Zendy; Satoshi Kodera | Zendy; Masataka Satô | Zendy; Susumu Katsushika | Zendy; Issei Sukeda | Zendy; Hirotoshi Takeuchi | Zendy; Hiroki Shinohara | Zendy; Atsushi Kobayashi | Zendy; Hiroshi Takiguchi | Zendy; Kazutoshi Hirose | Zendy; Tatsuya Kamon | Zendy; Akihito Saito | Zendy; Hiroyuki Kiriyama | Zendy; Mizuki Miura | Zendy; Shun Minatsuki | Zendy; Hironobu Kikuchi | Zendy; Yasutomi Higashikuni | Zendy; Norifumi Takeda | Zendy; Katsuhito Fujiu | Zendy; Jiro Ando | Zendy; Hiroshi Akazawa | Zendy; Hiroyuki Morita | Zendy; Issei Komuro | Zendy

Open Access

Age prediction from coronary angiography using a deep neural network: Age as a potential label to extract prognosis-related imaging features

Author(s) -

Shinnosuke Sawano,

Satoshi Kodera,

Masataka Satô,

Susumu Katsushika,

Issei Sukeda,

Hirotoshi Takeuchi,

Hiroki Shinohara,

Atsushi Kobayashi,

Hiroshi Takiguchi,

Kazutoshi Hirose,

Tatsuya Kamon,

Akihito Saito,

Hiroyuki Kiriyama,

Mizuki Miura,

Shun Minatsuki,

Hironobu Kikuchi,

Yasutomi Higashikuni,

Norifumi Takeda,

Katsuhito Fujiu,

Jiro Ando,

Hiroshi Akazawa,

Hiroyuki Morita,

Issei Komuro

Publication year - 2022

Publication title -

plos one

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.99

H-Index - 332

ISSN - 1932-6203

DOI - 10.1371/journal.pone.0276928

Subject(s) - percutaneous coronary intervention , medicine , conventional pci , mace , cardiology , hazard ratio , acute coronary syndrome , coronary arteries , coronary artery disease , proportional hazards model , artery , confidence interval , myocardial infarction

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