A Systematic Review of Advances in AI-Assisted Analysis of Fundus Fluorescein Angiography (FFA) Images: From Detection to Report Generation.

Fundus fluorescein angiography (FFA) serves as the current gold standard for visualizing retinal vasculature and detecting various fundus diseases, but its interpretation is labor-intensive and requires much expertise from ophthalmologists. The medical application of artificial intelligence (AI), especially deep learning and machine learning, has revolutionized the field of automatic FFA image analysis, leading to the rapid advancements in AI-assisted lesion detection, diagnosis, and report generation. This review examined studies in PubMed, Web of Science, and Google Scholar databases from January 2019 to August 2024, with a total of 23 articles incorporated.

Assessment of Large Language Models in Cataract Care Information Provision: A Quantitative Comparison.

Introduction: Cataracts are a significant cause of blindness. While individuals frequently turn to the Internet for medical advice, distinguishing reliable information can be challenging. Large language models (LLMs) have attracted attention for generating accurate, human-like responses that may be used for medical consultation.