509 citations · 1.3k across the 14 of their papers we have counts for
5 papers · 1 filter
Robust and Efficient Medical Imaging with Self-Supervision
Shekoofeh Azizi, Laura Culp, Jan Freyberg +31
Recent progress in Medical Artificial Intelligence (AI) has delivered systems that can reach clinical expert level performance. However, such systems tend to demonstrate sub-optima…
Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading
Ellery Wulczyn, Kunal Nagpal, Matthew Symonds +20
Gleason grading of prostate cancer is an important prognostic factor but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial i…
Multimodal Multitask Representation Learning for Pathology Biobank Metadata Prediction
Wei-Hung Weng, Yuannan Cai, Angela Lin +2
Metadata are general characteristics of the data in a well-curated and condensed format, and have been proven to be useful for decision making, knowledge discovery, and also hetero…
Whole-Slide Image Focus Quality: Automatic Assessment and Impact on AI Cancer Detection
Timo Kohlberger, Yun Liu, Melissa Moran +6
Digital pathology enables remote access or consults and powerful image analysis algorithms. However, the slide digitization process can create artifacts such as out-of-focus (OOF).…
Development and Validation of a Deep Learning Algorithm for Improving Gleason Scoring of Prostate Cancer
Kunal Nagpal, Davis Foote, Yun Liu +17
For prostate cancer patients, the Gleason score is one of the most important prognostic factors, potentially determining treatment independent of the stage. However, Gleason scorin…