Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer

For prostate cancer patients, the Gleason score is one of the most important prognostic factors, potentially determining treatment independent of the stage. However, Gleason scoring is based on subjective microscopic examination of tumor morphology and suffers from poor reproducibility. Here we pres...

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Veröffentlicht in:NPJ Digit Med
Hauptverfasser: Nagpal, Kunal, Foote, Davis, Liu, Yun, Chen, Po-Hsuan Cameron, Wulczyn, Ellery, Tan, Fraser, Olson, Niels, Smith, Jenny L., Mohtashamian, Arash, Wren, James H., Corrado, Greg S., MacDonald, Robert, Peng, Lily H., Amin, Mahul B., Evans, Andrew J., Sangoi, Ankur R., Mermel, Craig H., Hipp, Jason D., Stumpe, Martin C.
Format: Artigo
Sprache:Inglês
Veröffentlicht: Nature Publishing Group UK 2019
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Article
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6555810/
https://ncbi.nlm.nih.gov/pubmed/31304394
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41746-019-0112-2
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