K
Kornwipa Hemarat
Researcher at Vajira Hospital
Publications - 4
Citations - 204
Kornwipa Hemarat is an academic researcher from Vajira Hospital. The author has contributed to research in topics: Diabetic retinopathy & Population. The author has an hindex of 3, co-authored 3 publications receiving 110 citations.
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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
Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study.
Paisan Ruamviboonsuk,Richa Tiwari,Rory Sayres,Variya Nganthavee,Kornwipa Hemarat,Apinpat Kongprayoon,Rajiv Raman,Brian Levinstein,Yun Liu,Mike Schaekermann,R. Lee,Sunny Virmani,Kasumi Widner,John S. Chambers,Fred Hersch,Lily Peng,Dale R. Webster +16 more
TL;DR: In this paper , a prospective interventional cohort study to evaluate the real-world performance and feasibility of deploying a deep-learning system into the health-care system of Thailand was conducted, where eligible patients were screened with the deep learning system at nine primary care sites under Thailand's national diabetic retinopathy screening programme.
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.
Posted Content
Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening Program
Paisan Raumviboonsuk,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 Sukulmalpaiboon,Chainarong Luengchaichawang,Jitumporn Fuangkaew,Pipat Kongsap,Lamyong Chualinpha,Sarawuth Saree,Srirat 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, suggesting that deep learning algorithms may serve as a valuable tool for DR screening.