1.9k citations · 5.9k across the 23 of their papers we have counts for
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Deep learning for predicting refractive error from retinal fundus images
Avinash V. Varadarajan, Ryan Poplin, Katy Blumer +7
Refractive error, one of the leading cause of visual impairment, can be corrected by simple interventions like prescribing eyeglasses. We trained a deep learning algorithm to predi…
Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy
Jonathan Krause, Varun Gulshan, Ehsan Rahimy +5
Diabetic retinopathy (DR) and diabetic macular edema are common complications of diabetes which can lead to vision loss. The grading of DR is a fairly complex process that requires…
Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs using Deep Learning
Ryan Poplin, Avinash V. Varadarajan, Katy Blumer +5
Traditionally, medical discoveries are made by observing associations and then designing experiments to test these hypotheses. However, observing and quantifying associations in im…
Detecting Cancer Metastases on Gigapixel Pathology Images
Yun Liu, Krishna Gadepalli, Mohammad Norouzi +10
Each year, the treatment decisions for more than 230,000 breast cancer patients in the U.S. hinge on whether the cancer has metastasized away from the breast. Metastasis detection…