Artificial intelligence for telemedicine diabetic retinopathy screening: a review.

Luis Filipe Nakayama Lucas Zago Ribeiro Frederico Novaes Isabele Ayumi Miyawaki Andresa Emy Miyawaki Juliana Angélica Estevão Oliveira Talita Virgínia Fernandes de Oliveira Fernando Korn Malerbi Caio Vinicius Saito Regatieri Leo Anthony Celi Paolo S Silva

Published in: Annals of medicine (2023)

Telemedicine and AI hold great promise for augmenting decision-making in medical care, expanding patient access and enhancing cost-effectiveness. Economic studies and social science analysis are crucial to support the implementation of AI in teleophthalmology screening programs. Promoting fairness and generalizability in automated systems combined with telemedicine screening programs is not straightforward. Improving data representativeness, reducing biases and promoting equity in deployment and post-deployment studies are all critical steps in model development.

Keyphrases

artificial intelligence
big data
diabetic retinopathy
machine learning
deep learning
public health
healthcare
optical coherence tomography
primary care
electronic health record
mental health
high throughput
quality improvement