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Ophthalmologists

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Comparison of ChatGPT-4o, Google Gemini 1.5 Pro, Microsoft Copilot Pro, and Ophthalmologists in the management of uveitis and ocular inflammation: A comparative study of large language models.

Journal francais d'ophtalmologie
PURPOSE: The aim of this study was to compare the latest large language models (LLMs) ChatGPT-4o, Google Gemini 1.5 Pro and Microsoft Copilot Pro developed by three different companies, with each other and with a group of ophthalmologists, to reveal ...

A Preliminary Evaluation of the Diagnostic Performance of a Smartphone-Based Machine Learning-Assisted System for Evaluation of Clinical Activity Score in Digital Images of Thyroid-Associated Orbitopathy.

Thyroid : official journal of the American Thyroid Association
We previously developed a machine learning (ML)-assisted system for predicting the clinical activity score (CAS) in thyroid-associated orbitopathy (TAO) using digital facial images taken by a digital single-lens reflex camera in a studio setting. In...

The role of saliency maps in enhancing ophthalmologists' trust in artificial intelligence models.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: Saliency maps (SM) allow clinicians to better understand the opaque decision-making process in artificial intelligence (AI) models by visualising the important features responsible for predictions. This ultimately improves interpretability a...

The use of artificial intelligence based chat bots in ophthalmology triage.

Eye (London, England)
PURPOSE: To evaluate AI-based chat bots ability to accurately answer common patient's questions in the field of ophthalmology.

Using machine learning to identify pediatric ophthalmologists.

Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus
This cross-sectional study used data from the American Academy of Ophthalmology IRIS Registry (Intelligent Research in Sight) and machine learning algorithms to identify pediatric ophthalmologists based on physician coding patterns. A random forest m...

Influence of artificial intelligence on ophthalmologists' judgments in glaucoma.

PloS one
PURPOSE: To examine the influence of artificial intelligence (AI) on physicians' judgments regarding the presence and severity of glaucoma on fundus photographs in an online simulation system.

The importance of clinical experience in AI-assisted corneal diagnosis: verification using intentional AI misleading.

Scientific reports
We developed an AI system capable of automatically classifying anterior eye images as either normal or indicative of corneal diseases. This study aims to investigate the influence of AI's misleading guidance on ophthalmologists' responses. This cross...

Artificial intelligence support improves diagnosis accuracy in anterior segment eye diseases.

Scientific reports
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...

Stakeholder Attitudes on AI Integration in Ophthalmology.

Klinische Monatsblatter fur Augenheilkunde
Artificial intelligence (AI) is gaining widespread traction in ophthalmology, with multiple screening and diagnostic tools already being approved by U. S. and EU authorities. However, the adoption of these tools among medical professionals and their ...

The potential of artificial intelligence reading label system on the training of ophthalmologists in retinal diseases, a multicenter bimodal multi-disease study.

BMC medical education
OBJECTIVE: To assess the potential of artificial intelligence reading label system on the training of ophthalmologists in a multicenter bimodal multi-disease study.