Medical artificial intelligence (AI) offers great potential for recognizing signs of health
conditions in retinal images and expediting the diagnosis of eye diseases and systemic …

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 …

The healthcare burden of cardiovascular diseases remains a major issue worldwide.
Understanding the underlying mechanisms and improving identification of people with a …

Aims We examine whether inclusion of artificial intelligence (AI)-enabled retinal
vasculometry (RV) improves existing risk algorithms for incident stroke, myocardial infarction …

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

Cardiovascular diseases (CVDs) are one of the most prevalent causes of premature death.
Early detection is crucial to prevent and address CVDs in a timely manner. Recent advances …

Clinical decision support systemsthat use artificial intelligence (AI) to improve diagnostic
accuracy, efficiency, and safety have long been aspirational goals for computer scientists …

Retinal vascular diseases represent a broad field of ocular pathologies. Retinal imaging is
an important tool for diagnosis, prognosis and follow up of retinal vascular diseases. It …

Characterizing thermally sprayed coatings remains challenging due to the interplay between
different operating and process parameters. Currently, no general framework exists for …

The advent of artificial intelligence (AI), especially the state-of-the-art deep learning
frameworks, has begun a silent revolution in all medical subfields, including ophthalmology …