S
Sonia Phene
Researcher at Google
Publications - 11
Citations - 360
Sonia Phene is an academic researcher from Google. The author has contributed to research in topics: Glaucoma & Fundus (eye). The author has an hindex of 5, co-authored 11 publications receiving 190 citations.
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Journal ArticleDOI
Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.
Sonia Phene,R. Carter Dunn,Naama Hammel,Yun Liu,Jonathan Krause,Naho Kitade,Mike Schaekermann,Rory Sayres,Derek Wu,Ashish Bora,Christopher Semturs,Anita Misra,Abigail E. Huang,Arielle Spitze,Felipe A. Medeiros,April Y. Maa,Monica Gandhi,Greg S. Corrado,Lily Peng,Dale R. Webster +19 more
TL;DR: A deep learning algorithm trained on fundus images alone can detect referable GON with higher sensitivity than and comparable specificity to eye care providers and maintained good performance on an independent dataset with diagnoses based on a full glaucoma workup.
Journal ArticleDOI
Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program.
Paisan Ruamviboonsuk,Jonathan Krause,Peranut Chotcomwongse,Rory Sayres,Rajiv Raman,Kasumi Widner,Bilson J. L. Campana,Sonia Phene,Kornwipa Hemarat,Mongkol Tadarati,Sukhum Silpa-archa,Jirawut Limwattanayingyong,Chetan Rao,Oscar Kuruvilla,Jesse J. Jung,Jeffrey Tan,Surapong Orprayoon,Chawawat Kangwanwongpaisan,Ramase Sukumalpaiboon,Chainarong Luengchaichawang,Jitumporn Fuangkaew,Pipat Kongsap,Lamyong Chualinpha,Sarawuth Saree,Srirut Kawinpanitan,Korntip Mitvongsa,Siriporn Lawanasakol,Chaiyasit Thepchatri,Lalita Wongpichedchai,Greg S. Corrado,Lily Peng,Dale R. Webster +31 more
TL;DR: Across different severity levels of DR for determining referable disease, deep learning significantly reduced the false negative rate at the cost of slightly higher false positive rates (2%).
Journal ArticleDOI
Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology.
Babak Alipanahi,Farhad Hormozdiari,Babak Behsaz,Justin Cosentino,Zachary R. McCaw,Emanuel Schorsch,D. Sculley,Elizabeth H. Dorfman,Paul J. Foster,Lily Peng,Sonia Phene,Naama Hammel,Andrew Carroll,Anthony P Khawaja,Cory Y. McLean +14 more
TL;DR: In this article, a machine learning model was used to predict glaucomatous optic nerve head features from color fundus photographs in the UK Biobank (UKB) for predicting vertical cup-to-disc ratio (VCDR), a diagnostic parameter and cardinal endophenotype for Glaucoma.
Posted Content
Large-scale machine learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology
Babak Alipanahi,Farhad Hormozdiari,Babak Behsaz,Justin Cosentino,Zachary R. McCaw,Emanuel Schorsch,D. Sculley,Elizabeth H. Dorfman,Sonia Phene,Naama Hammel,Andrew Carroll,Anthony P Khawaja,Cory Y. McLean +12 more
TL;DR: A machine learning (ML) model is developed to predict glaucomatous optic nerve head features from color fundus photographs to significantly improve polygenic prediction of VCDR and primary open-angleglaucoma in the independent EPIC-Norfolk cohort.
Journal ArticleDOI
Author Correction: Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program
Paisan Ruamviboonsuk,Jonathan Krause,Peranut Chotcomwongse,Rory Sayres,Rajiv Raman,Kasumi Widner,Bilson J. L. Campana,Sonia Phene,Kornwipa Hemarat,Mongkol Tadarati,Sukhum Silpa-archa,Jirawut Limwattanayingyong,Chetan Rao,Oscar Kuruvilla,Jesse J. Jung,Jeffrey Tan,Surapong Orprayoon,Chawawat Kangwanwongpaisan,Ramase Sukumalpaiboon,Chainarong Luengchaichawang,Jitumporn Fuangkaew,Pipat Kongsap,Lamyong Chualinpha,Sarawuth Saree,Srirut Kawinpanitan,Korntip Mitvongsa,Siriporn Lawanasakol,Chaiyasit Thepchatri,Lalita Wongpichedchai,Greg S. Corrado,Lily Peng,Dale R. Webster +31 more
TL;DR: An amendment to this paper has been published and can be accessed via a link at the top of the paper.