Interpretable survival prediction for colorectal cancer using deep learning

Deriving interpretable prognostic features from deep-learning-based prognostic histopathology models remains a challenge. In this study, we developed a deep learning system (DLS) for predicting disease-specific survival for stage II and III colorectal cancer using 3652 cases (27,300 slides). When ev...

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Vydáno v:NPJ Digit Med
Hlavní autoři: Wulczyn, Ellery, Steiner, David F., Moran, Melissa, Plass, Markus, Reihs, Robert, Tan, Fraser, Flament-Auvigne, Isabelle, Brown, Trissia, Regitnig, Peter, Chen, Po-Hsuan Cameron, Hegde, Narayan, Sadhwani, Apaar, MacDonald, Robert, Ayalew, Benny, Corrado, Greg S., Peng, Lily H., Tse, Daniel, Müller, Heimo, Xu, Zhaoyang, Liu, Yun, Stumpe, Martin C., Zatloukal, Kurt, Mermel, Craig H.
Médium: Artigo
Jazyk:Inglês
Vydáno: Nature Publishing Group UK 2021
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Article
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC8055695/
https://ncbi.nlm.nih.gov/pubmed/33875798
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41746-021-00427-2
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