We summarize an overview of the key concepts, and categorize some examples of
commonly employed XAI methods. Specific to ophthalmology, we explore XAI from a clinical …

The emergence of generative artificial intelligence (AI) has revolutionized various fields. In
ophthalmology, generative AI has the potential to enhance efficiency, accuracy …

Cardiovascular disease (CVD) is a major cause of mortality and morbidity worldwide and
imposes significant socioeconomic burdens, especially with late diagnoses. There is …

Purpose This narrative review aims to provide an overview of the dangers, controversial
aspects, and implications of artificial intelligence (AI) use in ophthalmology and other …

Aim: To describe barriers to implementation of diabetic retinopathy (DR) teleretinal
screening programs and artificial intelligence (AI) integration at the University of California …

Current status and practical considerations of artificial in... : Current Opinion in
Ophthalmology Current status and practical considerations of artificial intelligence use in …

The integration of artificial intelligence (AI) in ophthalmology has promoted the development
of the discipline, offering opportunities for enhancing diagnostic accuracy, patient care, and …

Artificial Intelligence (AI) is transforming healthcare, notably in ophthalmology, where its
ability to interpret images and data can significantly enhance disease diagnosis and patient …

The rapid advancement and integration of artificial intelligence (AI) in various domains of
society have given rise to a complex landscape of public concerns. This research endeavors …

Purpose: This study developed machine learning (ML) classifiers of postoperative corneal
endothelial cell images to identify postkeratoplasty patients at risk for allograft rejection …