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Ophthalmology
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March 18, 2018
Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy
Jonathan 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 India
Varun Gulshan, Renu P Rajan, Kasumi Widner, et al.
Nature Medicine
|
May 29, 2023
Lessons learned from translating AI from development to deployment in healthcare
Kasumi 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 Photographs
Varun 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 study
Paisan Ruamviboonsuk, Richa Tiwari, Rory Sayres, et al.
JAMA Network Open
|
March 19, 2025
Performance of a Deep Learning Diabetic Retinopathy Algorithm in India
Arthur 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 Diabetes
Antonio 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 program
Paisan 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 program
Paisan Ruamviboonsuk, Jonathan Krause, Peranut Chotcomwongse, et al.
Page
of 1
Search research articles
Search
Showing results (1-10 of 9) with videos related to
Sort By:
Page
of 1
Ophthalmology
|
March 18, 2018
Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy
Jonathan 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 India
Varun Gulshan, Renu P Rajan, Kasumi Widner, et al.
Nature Medicine
|
May 29, 2023
Lessons learned from translating AI from development to deployment in healthcare
Kasumi 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 Photographs
Varun 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 study
Paisan Ruamviboonsuk, Richa Tiwari, Rory Sayres, et al.
JAMA Network Open
|
March 19, 2025
Performance of a Deep Learning Diabetic Retinopathy Algorithm in India
Arthur 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 Diabetes
Antonio 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 program
Paisan 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 program
Paisan Ruamviboonsuk, Jonathan Krause, Peranut Chotcomwongse, et al.
Page
of 1