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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Dades bibliogràfiques
Publicat a:NPJ Digit Med
Autors principals: 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
Idioma:Inglês
Publicat: Nature Publishing Group UK 2019
Matèries:
Article
Accés en línia: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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