|Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs|
V Gulshan, L Peng, M Coram, MC Stumpe, D Wu, A Narayanaswamy, ...
jama 316 (22), 2402-2410, 2016
|Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathy|
J Krause, V Gulshan, E Rahimy, P Karth, K Widner, GS Corrado, L Peng, ...
Ophthalmology 125 (8), 1264-1272, 2018
|Performance of a deep-learning algorithm vs manual grading for detecting diabetic retinopathy in India|
V Gulshan, RP Rajan, K Widner, D Wu, P Wubbels, T Rhodes, ...
JAMA ophthalmology 137 (9), 987-993, 2019
|Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program|
P Ruamviboonsuk, J Krause, P Chotcomwongse, R Sayres, R Raman, ...
NPJ digital medicine 2 (1), 25, 2019
|Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study|
P Ruamviboonsuk, R Tiwari, R Sayres, V Nganthavee, K Hemarat, ...
The Lancet Digital Health 4 (4), e235-e244, 2022
|Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening Program|
P Raumviboonsuk, J Krause, P Chotcomwongse, R Sayres, R Raman, ...
arXiv preprint arXiv:1810.08290, 2018
|Lessons learned from translating AI from development to deployment in healthcare|
K Widner, S Virmani, J Krause, J Nayar, R Tiwari, ER Pedersen, D Jeji, ...
Nature Medicine, 1-3, 2023
|Challenges in evaluating clinical deployments of deep learning assisted diagnostics for diabetic retinopathy screening|
G Wolff, R Sayres, V Gulshan, K Widner, J Krause, D Jadeja, ...
Investigative Ophthalmology & Visual Science 61 (7), 2045-2045, 2020