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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...
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. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Association
2020
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Materias: | |
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 |
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