Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading

no code implementations • 25 Nov 2020 • Ellery Wulczyn, Kunal Nagpal, Matthew Symonds, Melissa Moran, Markus Plass, Robert Reihs, Farah Nader, Fraser Tan, Yuannan Cai, Trissia Brown, Isabelle Flament-Auvigne, Mahul B. Amin, Martin C. Stumpe, Heimo Muller, Peter Regitnig, Andreas Holzinger, Greg S. Corrado, Lily H. Peng, Po-Hsuan Cameron Chen, David F. Steiner, Kurt Zatloukal, Yun Liu, Craig H. Mermel

's C-indices were 0. 87 and 0. 85 for continuous and discrete grading, respectively, compared to 0. 79 (95%CI 0. 71-0. 86) for GG obtained from the reports.

Management Open-Ended Question Answering

Similar Image Search for Histopathology: SMILY

no code implementations • 30 Jan 2019 • Narayan Hegde, Jason D. Hipp, Yun Liu, Michael E. Buck, Emily Reif, Daniel Smilkov, Michael Terry, Carrie J. Cai, Mahul B. Amin, Craig H. Mermel, Phil Q. Nelson, Lily H. Peng, Greg S. Corrado, Martin C. Stumpe

SMILY may be a useful general-purpose tool in the pathologist's arsenal, to improve the efficiency of searching large archives of histopathology images, without the need to develop and implement specific tools for each application.

Image Retrieval

Development and Validation of a Deep Learning Algorithm for Improving Gleason Scoring of Prostate Cancer

no code implementations • 15 Nov 2018 • Kunal Nagpal, Davis Foote, Yun Liu, Po-Hsuan, Chen, Ellery Wulczyn, Fraser Tan, Niels Olson, Jenny L. Smith, Arash Mohtashamian, James H. Wren, Greg S. Corrado, Robert MacDonald, Lily H. Peng, Mahul B. Amin, Andrew J. Evans, Ankur R. Sangoi, Craig H. Mermel, Jason D. Hipp, Martin C. Stumpe

For prostate cancer patients, the Gleason score is one of the most important prognostic factors, potentially determining treatment independent of the stage.

whole slide images