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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Bibliografske podrobnosti
izdano v:NPJ Digit Med
Main Authors: 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.
Format: Artigo
Jezik:Inglês
Izdano: Nature Publishing Group UK 2021
Teme:
Article
Online dostop: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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