Deep-learning algorithm to detect fibrosing interstitial lung disease on chest radiographs

被引：18

作者：

Nishikiori, Hirotaka ^{[1
]}

Kuronuma, Koji ^{[1
]}

Hirota, Kenichi ^{[2
]}

Yama, Naoya ^{[3
]}

Suzuki, Tomohiro ^{[4
]}

Onodera, Maki ^{[3
]}

Onodera, Koichi ^{[3
]}

Ikeda, Kimiyuki ^{[1
]}

Mori, Yuki ^{[1
]}

Asai, Yuichiro ^{[1
]}

Takagi, Yuzo ^{[5
]}

Honda, Seiwa ^{[4
]}

Ohnishi, Hirofumi ^{[6
]}

Hatakenaka, Masamitsu ^{[3
]}

Takahashi, Hiroki ^{[1
]}

Chiba, Hirofumi ^{[1
]}

机构：

[1] Sapporo Med Univ, Sch Med, Dept Resp Med & Allergol, Sapporo, Japan

[2] Sapporo Med Univ Hosp, Dept Med Informat Planning, Sapporo, Japan

[3] Sapporo Med Univ, Sch Med, Dept Diagnost Radiol, Sapporo, Japan

[4] M3 Inc, Tokyo, Japan

[5] SEEDSUPPLY Inc, Fujisawa, Kanagawa, Japan

[6] Sapporo Med Univ, Sch Med, Dept Publ Hlth, Sapporo, Japan

来源：

EUROPEAN RESPIRATORY JOURNAL | 2023年 / 61卷 / 02期

关键词：

CLASSIFICATION; PNEUMONIA;

D O I：

10.1183/13993003.02269-2021

中图分类号：

R56 [呼吸系及胸部疾病];

学科分类号：

摘要：

A deep-learning algorithm was developed to detect fibrotic interstitial lung disease using chest radiographs. The algorithm's detection capability was noninferior to that of doctors, including pulmonologists and radiologists. https://bit.ly/3SAClW2

引用

页数：10

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