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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555810/
https://www.ncbi.nlm.nih.gov/pubmed/31304394
http://dx.doi.org/10.1038/s41746-019-0112-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555810/
https://www.ncbi.nlm.nih.gov/pubmed/31304394
http://dx.doi.org/10.1038/s41746-019-0112-2

Ejemplares similares