Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes predicts survival after immune checkpoint inhibitor therapy across multiple cancer types.

被引：2

作者：

Shen, Jeanne

Lee, Taebum

Hwang, Jun-Eul

Choi, Yoon-La

Lee, Se-Hoon

Kim, Hyojin

Chung, Jin-haeng

Bogdan, Stephanie

Huang, Maggie

Raclin, Tyler

Fisher, George A.

Pereira, Sergio

Park, Seonwook

Ma, Minuk

Yoo, Donggeun

Shin, Seunghwan

Paeng, Kyunghyun

Ock, Chan-Young

Mok, Tony S. K.

Bang, Yung-Jue

机构：

[1] Stanford Univ, Sch Med, Dept Pathol, Stanford, CA 94305 USA

[2] Chonnam Natl Univ Hosp, Dept Pathol, Gwangju, South Korea

[3] Chonnam Natl Univ, Sch Med, Dept Internal Med, Div Hematol Oncol, Gwangju, South Korea

[4] Sungkyunkwan Univ, Sch Med, Samsung Med Ctr, Dept Pathol & Translat Med, Seoul, South Korea

[5] Sungkyunkwan Univ, Sch Med, Samsung Med Ctr, Div Hematol & Oncol,Dept Med, Seoul, South Korea

[6] Seoul Natl Univ, Bundang Hosp, Dept Pathol, Seongnam, South Korea

[7] Stanford Univ, Sch Med, Ctr Artificial Intelligence Med & Imaging, Stanford, CA 94305 USA

[8] UC Davis Hlth, Davis, CA USA

[9] Stanford Univ, Sch Med, Stanford, CA 94305 USA

[10] Stanford Univ, Dept Med, Stanford, CA 94305 USA

[11] Lunit Inc, Seoul, South Korea

[12] Chinese Univ Hong Kong, State Key Lab Translat Oncol, Hong Kong, Peoples R China

[13] Seoul Natl Univ, Coll Med, Seoul, South Korea

来源：

JOURNAL OF CLINICAL ONCOLOGY | 2021年 / 39卷 / 15期

关键词：

D O I：

10.1200/JCO.2021.39.15_suppl.2607

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

2607

引用

页数：2

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