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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…
Large-scale machine learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology
Babak Alipanahi, Farhad Hormozdiari, Babak Behsaz +10
Genome-wide association studies (GWAS) require accurate cohort phenotyping, but expert labeling can be costly, time-intensive, and variable. Here we develop a machine learning (ML)…
Detecting hidden signs of diabetes in external eye photographs
Boris Babenko, Akinori Mitani, Ilana Traynis +10
Diabetes-related retinal conditions can be detected by examining the posterior of the eye. By contrast, examining the anterior of the eye can reveal conditions affecting the front…
Interpretable Survival Prediction for Colorectal Cancer using Deep Learning
Ellery Wulczyn, David F. Steiner, Melissa Moran +20
Deriving interpretable prognostic features from deep-learning-based prognostic histopathology models remains a challenge. In this study, we developed a deep learning system (DLS) f…
Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases
Zaid Nabulsi, Andrew Sellergren, Shahar Jamshy +20
Chest radiography (CXR) is the most widely-used thoracic clinical imaging modality and is crucial for guiding the management of cardiothoracic conditions. The detection of specific…
Predicting Risk of Developing Diabetic Retinopathy using Deep Learning
Ashish Bora, Siva Balasubramanian, Boris Babenko +13
Diabetic retinopathy (DR) screening is instrumental in preventing blindness, but faces a scaling challenge as the number of diabetic patients rises. Risk stratification for the dev…
Scientific Discovery by Generating Counterfactuals using Image Translation
Arunachalam Narayanaswamy, Subhashini Venugopalan, Dale R. Webster +10
Model explanation techniques play a critical role in understanding the source of a model's performance and making its decisions transparent. Here we investigate if explanation tech…