The rapid progress of large language models (LLMs) driving generative artificial intelligence
applications heralds the potential of opportunities in health care. We conducted a review up …

Progress in artificial intelligence and tele-ophthalmology for diabetic retinopathy screening,
including artificial intelligence applications in 'real-world settings' and cost-effectiveness …

The volume and complexity of diagnostic imaging is increasing at a pace faster than the
availability of human expertise to interpret it. Artificial intelligence has shown great promise …

Deep learning may transform health care, but model development has largely been
dependent on availability of advanced technical expertise. Herein we present the …

Deep learning of artificial neural networks has become the de facto standard approach to
solving data analysis problems in virtually all fields of science and engineering. Also in …

The trustworthiness (or otherwise) of AI has been much in discussion of late, not least
because of the recent publication of the EU Guidelines for Trustworthy AI. Discussions range …

Optical coherence tomography (OCT) is an imaging modality used to obtain a cross-
sectional image of the retina for retinal disease diagnosis. Modern diagnosis systems use …

Cardiovascular disease (CVD) remains the leading cause of death worldwide. Assessing of
CVD risk plays an essential role in identifying individuals at higher risk and enables the …

Artificial intelligence based retinal microvasculature analysis may supplement existing CVD
risk stratification approach. Although technical and socioeconomic challenges remain, we …

As a third of people with diabetes mellitus (DM) will suffer the microvascular complications of
diabetic retinopathy (DR) and therapeutic options can effectively prevent visual impairment …