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Greg S Corrado

Showing results (11-20 of 66) with videos related to

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Investigative Ophthalmology & Visual Science|July 20, 2018
Deep Learning for Predicting Refractive Error From Retinal Fundus ImagesAvinash V Varadarajan, Ryan Poplin, Katy Blumer, et al.
Nature Biomedical Engineering|March 30, 2022
Detection of signs of disease in external photographs of the eyes via deep learningBoris Babenko, Akinori Mitani, Ilana Traynis, et al.
Translational Vision Science & Technology|December 11, 2023
Risk Stratification for Diabetic Retinopathy Screening Order Using Deep Learning: A Multicenter Prospective StudyAshish Bora, Richa Tiwari, Pinal Bavishi, et al.
Nature Medicine|August 14, 2019
An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosisPo-Hsuan Cameron Chen, Krishna Gadepalli, Robert MacDonald, et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc|September 12, 2025
PolyPath: Adapting a Large Multimodal Model for Multislide Pathology Report GenerationFaruk Ahmed, Lin Yang, Tiam Jaroensri, et al.
Translational Vision Science & Technology|December 24, 2019
Remote Tool-Based Adjudication for Grading Diabetic RetinopathyMike Schaekermann, Naama Hammel, Michael Terry, et al.
PLOS Global Public Health|June 4, 2024
Predicting cardiovascular disease risk using photoplethysmography and deep learningWei-Hung Weng, Sebastien Baur, Mayank Daswani, et al.
JAMA Dermatology|April 15, 2026
Consumer Understanding of Skin Concerns With an AI-Powered Informational ToolRory Sayres, Ayush Jain, Maya Venkatraman, et al.
Radiology|December 4, 2019
Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted EvaluationAnna Majkowska, Sid Mittal, David F Steiner, et al.
The Lancet. Digital Health|March 18, 2021
Predicting the risk of developing diabetic retinopathy using deep learningAshish Bora, Siva Balasubramanian, Boris Babenko, et al.
Pageof 7

Showing results (11-20 of 66) with videos related to

Sort By:
Pageof 7
Investigative Ophthalmology & Visual Science|July 20, 2018
Deep Learning for Predicting Refractive Error From Retinal Fundus ImagesAvinash V Varadarajan, Ryan Poplin, Katy Blumer, et al.
Nature Biomedical Engineering|March 30, 2022
Detection of signs of disease in external photographs of the eyes via deep learningBoris Babenko, Akinori Mitani, Ilana Traynis, et al.
Translational Vision Science & Technology|December 11, 2023
Risk Stratification for Diabetic Retinopathy Screening Order Using Deep Learning: A Multicenter Prospective StudyAshish Bora, Richa Tiwari, Pinal Bavishi, et al.
Nature Medicine|August 14, 2019
An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosisPo-Hsuan Cameron Chen, Krishna Gadepalli, Robert MacDonald, et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc|September 12, 2025
PolyPath: Adapting a Large Multimodal Model for Multislide Pathology Report GenerationFaruk Ahmed, Lin Yang, Tiam Jaroensri, et al.
Translational Vision Science & Technology|December 24, 2019
Remote Tool-Based Adjudication for Grading Diabetic RetinopathyMike Schaekermann, Naama Hammel, Michael Terry, et al.
PLOS Global Public Health|June 4, 2024
Predicting cardiovascular disease risk using photoplethysmography and deep learningWei-Hung Weng, Sebastien Baur, Mayank Daswani, et al.
JAMA Dermatology|April 15, 2026
Consumer Understanding of Skin Concerns With an AI-Powered Informational ToolRory Sayres, Ayush Jain, Maya Venkatraman, et al.
Radiology|December 4, 2019
Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted EvaluationAnna Majkowska, Sid Mittal, David F Steiner, et al.
The Lancet. Digital Health|March 18, 2021
Predicting the risk of developing diabetic retinopathy using deep learningAshish Bora, Siva Balasubramanian, Boris Babenko, et al.
Pageof 7