Middle East African journal of ophthalmology
39445000
PURPOSE: We aimed to evaluate the success of Chat Generative Pre-trained Transformer (ChatGPT), Bing, and Bard artificial intelligence programs, which were released free of charge by three different manufacturers, in correctly answering questions abo...
PURPOSE OF REVIEW: This review highlights the recent advancements in the applications of artificial intelligence within the field of cataract and refractive surgeries. Given the rapid evolution of artificial intelligence technologies, it is essential...
PURPOSE: The study explores the evolving landscape of cataract diagnosis, focusing on both traditional methods and innovative technological integrations. It aims to address challenges with subjectivity in traditional cataract grading and to evaluate ...
Diabetes has become a global epidemic, contributing to significant health challenges due to its complications. Among these, diabetes can affect sight through various mechanisms, emphasizing the importance of early identification and management of vi...
PURPOSE: To examine the performance of deep-learning models that predicts the visual acuity after cataract surgery using preoperative clinical information and color fundus photography (CFP).
International journal of medical sciences
40027191
Rat models are widely used to study cataracts due to their cost-effectiveness and prominent physiological and genetic similarities to humans The objective of this study was to identify genes involved in cataractogenesis due to galactose exposure in ...
OBJECTIVE: We compared the protein structure and pathogenicity of clinically relevant variants of the gene with AlphaFold2 (AF2), Alpha Missense (AM), and ThermoMPNN for the first time.
CorneAI, a deep learning model designed for diagnosing cataracts and corneal diseases, was assessed for its impact on ophthalmologists' diagnostic accuracy. In the study, 40 ophthalmologists (20 specialists and 20 residents) classified 100 images, in...
The variability in image modalities presents significant challenges in medical image classification, as traditional deep learning models often struggle to adapt to different image types, leading to suboptimal performance across diverse datasets. This...
Journal of cataract and refractive surgery
39680679
PURPOSE: To assess a new objective deep learning model cataract grading method based on swept-source optical coherence tomography (SS-OCT) scans provided by the Anterion.