Artificial Intelligence to Stratify Severity of Age-Related Macular Degeneration (AMD) and Predict Risk of Progression to Late AMD.

Journal: Translational vision science & technology

Published Date: Apr 24, 2020

Abstract

PURPOSE: To build and validate artificial intelligence (AI)-based models for AMD screening and for predicting late dry and wet AMD progression within 1 and 2 years.

Authors

Alauddin Bhuiyan
Tien Yin Wong

Singapore National Eye Center, Duke-National University of Singapore Medical School, Singapore 168751, Singapore; National Institutes of Health Research Biomedical Research Centre Biomedical Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
Daniel Shu Wei Ting

Singapore National Eye Center, Singapore Eye Research Institute Singapore Health Service Singapore Singapore.
Arun Govindaiah
Eric H Souied

Department of Ophthalmology, Hôpital Intercommunal de Créteil, Université, Creteil, France.
R Theodore Smith

Department of Ophthalmology, Icahn School of Medicine, Mount Sinai, NY, USA.

Keywords

Artificial Intelligence Fundus Oculi Humans Machine Learning Severity of Illness Index Wet Macular Degeneration

External Resources

View on PubMed Access via DOI PubMed (32818086)

Artificial Intelligence to Stratify Severity of Age-Related Macular Degeneration (AMD) and Predict Risk of Progression to Late AMD.

Abstract

Authors

Keywords

External Resources

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