While color fundus photos are used in routine clinical practice to diagnose ophthalmic
conditions, evidence suggests that ocular imaging contains valuable information regarding …

Background Stroke is a leading cause of morbidity and mortality. Retinal imaging allows non-
invasive assessment of the microvasculature. Consequently, retinal imaging is a technology …

Stroke stands as a major global health issue, causing high death and disability rates and
significant social and economic burdens. The effectiveness of existing stroke risk …

Rapid development in deep learning for image analysis inspired studies to focus on
predicting cardiovascular risk using retinal fundus images. This scoping review aimed to …

Artificial intelligence (AI) is the simulation of human intelligence by machines. This process
includes learning from constantly changing data and self-correction for improved decision …

Purpose: The purpose of this study was to perform a systematic review and meta-analysis to
synthesize evidence from studies using deep learning (DL) to predict cardiovascular …

Purpose: Current research on artificial intelligence–based fundus photography biomarkers
has demonstrated inconsistent results. Consequently, we aimed to evaluate and predict the …

Purpose: To develop a deep learning model to predict the risk of cardiovascular diseases
(CVDs) events based on features found in fundus images. Materials and Methods: We …