Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant–Positive Non–Small Cell Lung Cancer-Reference-Cited by-同舟云学术

Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant–Positive Non–Small Cell Lung Cancer

Published:2020-12-17 Issue:12 Volume:3 Page:e2030442
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

Song Jiangdian¹²,Wang Lu³,Ng Nathan Norton²,Zhao Mingfang⁴,Shi Jingyun⁵,Wu Ning⁶,Li Weimin⁷,Liu Zaiyi⁸,Yeom Kristen W.²,Tian Jie⁹

Affiliation:

1. School of Medical Informatics, China Medical University, Shenyang, Liaoning, China

2. Department of Radiology, School of Medicine Stanford University, Stanford, California

3. Department of Medical Informatics, China Medical University, Shenyang, Liaoning, China

4. Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning, China

5. Department of Radiology, Shanghai Pulmonary Hospital, Shanghai, China

6. National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

7. Department of Respiratory and Critical Care Medicine, West China Hospital, Chengdu, Sichuan, China

8. Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China

9. Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine and Engineering, Beihang University, Beijing, China

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2774288/song_2020_oi_200959_1613077574.3531.pdf

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