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Avinash V. Varadarajan
Researcher at Google
Publications - 33
Citations - 2764
Avinash V. Varadarajan is an academic researcher from Google. The author has contributed to research in topics: Fundus (eye) & Computer science. The author has an hindex of 12, co-authored 24 publications receiving 1694 citations. Previous affiliations of Avinash V. Varadarajan include University of California, Berkeley.
Papers
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Journal ArticleDOI
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning
Ryan Poplin,Avinash V. Varadarajan,Katy Blumer,Yun Liu,Michael V. McConnell,Greg S. Corrado,Lily Peng,Dale R. Webster +7 more
TL;DR: In this article, the authors used deep learning models trained on retinal fundus images to predict cardiovascular risk factors not previously thought to be present or quantifiable in retinal images.
Journal ArticleDOI
Predicting Cardiovascular Risk Factors in Retinal Fundus Photographs using Deep Learning
Ryan Poplin,Avinash V. Varadarajan,Katy Blumer,Yun Liu,Michael V. McConnell,Greg S. Corrado,Lily Peng,Dale R. Webster +7 more
TL;DR: Deep learning predicts, from retinal images, cardiovascular risk factors—such as smoking status, blood pressure and age—not previously thought to be present or quantifiable in these images.
Journal ArticleDOI
Deep learning in ophthalmology: The technical and clinical considerations.
Daniel Shu Wei Ting,Lily Peng,Avinash V. Varadarajan,Pearse A. Keane,Philippe Burlina,Michael F. Chiang,Leopold Schmetterer,Louis R. Pasquale,Neil M. Bressler,Dale R. Webster,Michael D. Abràmoff,Tien Yin Wong +11 more
TL;DR: Global eye disease burden, unmet needs and common conditions of public health importance for which AI and DL systems may be applicable are described and the potential challenges for clinical adoption are discussed.
Journal ArticleDOI
Deep Learning for Predicting Refractive Error From Retinal Fundus Images
Avinash V. Varadarajan,Ryan Poplin,Katy Blumer,Christof Angermueller,Joseph R. Ledsam,Reena Chopra,Pearse A. Keane,Greg S. Corrado,Lily Peng,Dale R. Webster +9 more
TL;DR: In this paper, a deep learning algorithm was used to predict refractive error from retinal fundus images and validated it on 24,007 UK Biobank and 15,750 AREDS images.
Journal ArticleDOI
Detecting Anemia from Retinal Fundus Images
Akinori Mitani,Yun Liu,Abigail E. Huang,Greg S. Corrado,Lily Peng,Dale R. Webster,Naama Hammel,Avinash V. Varadarajan +7 more
TL;DR: This work shows the potential of automated non-invasive anemia screening based on fundus images, particularly in diabetic patients, who may have regular retinal imaging and are at increased risk of further morbidity and mortality from anemia.