Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning

BACKGROUND: Identifying genetic mutations in cancer patients have been increasingly important because distinctive mutational patterns can be very informative to determine the optimal therapeutic strategy. Recent studies have shown that deep learning-based molecular cancer subtyping can be performed...

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Detalles Bibliográficos
Autores principales: Jang, Hyun-Jong, Lee, Ahwon, Kang, J, Song, In Hye, Lee, Sung Hak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2020
Materias:
Basic Study
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596644/
https://www.ncbi.nlm.nih.gov/pubmed/33177794
http://dx.doi.org/10.3748/wjg.v26.i40.6207

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596644/
https://www.ncbi.nlm.nih.gov/pubmed/33177794
http://dx.doi.org/10.3748/wjg.v26.i40.6207

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