Development and Validation of a Deep Learning Algorithm for Gleason Grading of Prostate Cancer From Biopsy Specimens

IMPORTANCE: For prostate cancer, Gleason grading of the biopsy specimen plays a pivotal role in determining case management. However, Gleason grading is associated with substantial interobserver variability, resulting in a need for decision support tools to improve the reproducibility of Gleason gra...

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Detalles Bibliográficos
Autores principales: Nagpal, Kunal, Foote, Davis, Tan, Fraser, Liu, Yun, Chen, Po-Hsuan Cameron, Steiner, David F., Manoj, Naren, Olson, Niels, Smith, Jenny L., Mohtashamian, Arash, Peterson, Brandon, Amin, Mahul B., Evans, Andrew J., Sweet, Joan W., Cheung, Carol, van der Kwast, Theodorus, Sangoi, Ankur R., Zhou, Ming, Allan, Robert, Humphrey, Peter A., Hipp, Jason D., Gadepalli, Krishna, Corrado, Greg S., Peng, Lily H., Stumpe, Martin C., Mermel, Craig H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2020
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378872/
https://www.ncbi.nlm.nih.gov/pubmed/32701148
http://dx.doi.org/10.1001/jamaoncol.2020.2485

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378872/
https://www.ncbi.nlm.nih.gov/pubmed/32701148
http://dx.doi.org/10.1001/jamaoncol.2020.2485

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