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

IMPORTANCE: An end-to-end efficacy evaluation approach for identifying progression risk after epidermal growth factor receptor (EGFR)–tyrosine kinase inhibitor (TKI) therapy in patients with stage IV EGFR variant–positive non–small cell lung cancer (NSCLC) is lacking. OBJECTIVE: To propose a clinica...

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Detalles Bibliográficos
Autores principales: Song, Jiangdian, Wang, Lu, Ng, Nathan Norton, Zhao, Mingfang, Shi, Jingyun, Wu, Ning, Li, Weimin, Liu, Zaiyi, Yeom, Kristen W., Tian, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2020
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7747022/
https://www.ncbi.nlm.nih.gov/pubmed/33331920
http://dx.doi.org/10.1001/jamanetworkopen.2020.30442

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7747022/
https://www.ncbi.nlm.nih.gov/pubmed/33331920
http://dx.doi.org/10.1001/jamanetworkopen.2020.30442

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