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Greg S. Corrado
Researcher at Google
Publications - 149
Citations - 114561
Greg S. Corrado is an academic researcher from Google. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 54, co-authored 125 publications receiving 95930 citations. Previous affiliations of Greg S. Corrado include IBM & Howard Hughes Medical Institute.
Papers
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Patent
Classifying data objects
Greg S. Corrado,Tomas Mikolov,Samy Bengio,Yoram Singer,Jonathon Shlens,Andrea Frome,Jeffrey Dean,Mohammad Norouzi +7 more
Posted Content
Detecting hidden signs of diabetes in external eye photographs.
Boris Babenko,Akinori Mitani,Ilana Traynis,Naho Kitade,Preeti Singh,April Y. Maa,Jorge Cuadros,Greg S. Corrado,Lily Peng,Dale R. Webster,Avinash V. Varadarajan,Naama Hammel,Yun Liu +12 more
TL;DR: The results indicate that external eye photographs contain information useful for healthcare providers managing patients with diabetes, and may help prioritize patients for in-person screening, as well as its utility for remote diagnosis and management.
Patent
Determining reply content for a reply to an electronic communication
Phillip Sharp,Prabhakar Raghavan,Gawley Thompson Alexander Ivor,Miklos Balint,Karol Kurach,Tobias Kaufmann,Greg S. Corrado,László Lukács +7 more
TL;DR: In this paper, reply content for a reply to an electronic communication is determined by analyzing a corpus of electronic communications to determine relationships between one or more original message features of "original" messages and reply content that is included in reply messages of those electronic communications.
Patent
Analyzing health events using recurrent neural networks
Greg S. Corrado,Jeffrey Dean +1 more
TL;DR: In this article, the first temporal sequence of health events is generated using a recurrent neural network (RNN) and health analysis data that characterizes future health events that may occur after a last time step in the temporal sequence.
Journal ArticleDOI
Predicting prostate cancer specific-mortality with artificial intelligence-based Gleason grading
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 Müller,Peter Regitnig,Andreas Holzinger,Greg S. Corrado,Lily Peng,Po-Hsuan Cameron Chen,David F. Steiner,Kurt Zatloukal,Yun Liu,Craig H. Mermel +22 more
TL;DR: Wulczyn et al. as discussed by the authors developed a system to predict prostate cancer-specific mortality via A.I. grading and subsequently evaluated its ability to risk-stratify patients on an independent retrospective cohort of 2807 prostatectomy cases from a single European center with 5-25 years of follow-up (median: 13, interquartile range 9-17).