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...

תיאור מלא

שמור ב:
מידע ביבליוגרפי
הוצא לאור ב:JAMA Oncol
Main Authors: 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.
פורמט: Artigo
שפה:Inglês
יצא לאור: American Medical Association 2020
נושאים:
Original Investigation
גישה מקוונת:https://ncbi.nlm.nih.gov/pmc/articles/PMC7378872/
https://ncbi.nlm.nih.gov/pubmed/32701148
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1001/jamaoncol.2020.2485
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