Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images

Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung cancer, with implications for patient prognosis and treatment decisions. Typically, TMB is evaluated by comprehensive genomic profiling but this requires use of finite tissue specimens and costly, time-co...

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Detalles Bibliográficos
Autores principales: Sadhwani, Apaar, Chang, Huang-Wei, Behrooz, Ali, Brown, Trissia, Auvigne-Flament, Isabelle, Patel, Hardik, Findlater, Robert, Velez, Vanessa, Tan, Fraser, Tekiela, Kamilla, Wulczyn, Ellery, Yi, Eunhee S., Mermel, Craig H., Hanks, Debra, Chen, Po-Hsuan Cameron, Kulig, Kimary, Batenchuk, Cory, Steiner, David F., Cimermancic, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8368039/
https://www.ncbi.nlm.nih.gov/pubmed/34400666
http://dx.doi.org/10.1038/s41598-021-95747-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8368039/
https://www.ncbi.nlm.nih.gov/pubmed/34400666
http://dx.doi.org/10.1038/s41598-021-95747-4

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