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Kasumi Widner

Showing results (1-10 of 9) with videos related to

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Ophthalmology|March 18, 2018
Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic RetinopathyJonathan Krause, Varun Gulshan, Ehsan Rahimy, et al.
JAMA Ophthalmology|June 14, 2019
Performance of a Deep-Learning Algorithm vs Manual Grading for Detecting Diabetic Retinopathy in IndiaVarun Gulshan, Renu P Rajan, Kasumi Widner, et al.
Nature Medicine|May 29, 2023
Lessons learned from translating AI from development to deployment in healthcareKasumi Widner, Sunny Virmani, Jonathan Krause, et al.
JAMA|November 30, 2016
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus PhotographsVarun Gulshan, Lily Peng, Marc Coram, et al.
The Lancet. Digital Health|March 11, 2022
Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort studyPaisan Ruamviboonsuk, Richa Tiwari, Rory Sayres, et al.
JAMA Network Open|March 19, 2025
Performance of a Deep Learning Diabetic Retinopathy Algorithm in IndiaArthur Brant, Preeti Singh, Xiang Yin, et al.
Ophthalmology and Therapy|March 15, 2025
Validation of a Deep Learning Model for Diabetic Retinopathy on Patients with Young-Onset DiabetesAntonio Tan-Torres, Pradeep A Praveen, Divleen Jeji, et al.
NPJ Digital Medicine|July 16, 2019
Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening programPaisan Raumviboonsuk, Jonathan Krause, Peranut Chotcomwongse, et al.
NPJ Digital Medicine|July 26, 2019
Erratum: Author Correction: Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening programPaisan Ruamviboonsuk, Jonathan Krause, Peranut Chotcomwongse, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Ophthalmology|March 18, 2018
Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic RetinopathyJonathan Krause, Varun Gulshan, Ehsan Rahimy, et al.
JAMA Ophthalmology|June 14, 2019
Performance of a Deep-Learning Algorithm vs Manual Grading for Detecting Diabetic Retinopathy in IndiaVarun Gulshan, Renu P Rajan, Kasumi Widner, et al.
Nature Medicine|May 29, 2023
Lessons learned from translating AI from development to deployment in healthcareKasumi Widner, Sunny Virmani, Jonathan Krause, et al.
JAMA|November 30, 2016
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus PhotographsVarun Gulshan, Lily Peng, Marc Coram, et al.
The Lancet. Digital Health|March 11, 2022
Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort studyPaisan Ruamviboonsuk, Richa Tiwari, Rory Sayres, et al.
JAMA Network Open|March 19, 2025
Performance of a Deep Learning Diabetic Retinopathy Algorithm in IndiaArthur Brant, Preeti Singh, Xiang Yin, et al.
Ophthalmology and Therapy|March 15, 2025
Validation of a Deep Learning Model for Diabetic Retinopathy on Patients with Young-Onset DiabetesAntonio Tan-Torres, Pradeep A Praveen, Divleen Jeji, et al.
NPJ Digital Medicine|July 16, 2019
Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening programPaisan Raumviboonsuk, Jonathan Krause, Peranut Chotcomwongse, et al.
NPJ Digital Medicine|July 26, 2019
Erratum: Author Correction: Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening programPaisan Ruamviboonsuk, Jonathan Krause, Peranut Chotcomwongse, et al.
Pageof 1