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
收藏
页数：2
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