AIMC Topic: Ophthalmology

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Translating the machine; An assessment of clinician understanding of ophthalmological artificial intelligence outputs.

International journal of medical informatics
INTRODUCTION: Advances in artificial intelligence offer the promise of automated analysis of optical coherence tomography (OCT) scans to detect ocular complications from anticancer drug therapy. To explore how such AI outputs are interpreted in clini...

Using large language models as decision support tools in emergency ophthalmology.

International journal of medical informatics
BACKGROUND: Large language models (LLMs) have shown promise in various medical applications, but their potential as decision support tools in emergency ophthalmology remains unevaluated using real-world cases.

Analysis of ChatGPT-4's performance on ophthalmology questions from the MIR exam.

Archivos de la Sociedad Espanola de Oftalmologia
PURPOSE: To evaluate the performance of ChatGPT in solving clinical scenarios in ophthalmology, specifically questions from the specialty exams for Resident Medical Interns (MIR).

Ethics of Artificial Intelligence in Medicine and Ophthalmology.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
BACKGROUND: This review explores the bioethical implementation of artificial intelligence (AI) in medicine and in ophthalmology. AI, which was first introduced in the 1950s, is defined as "the machine simulation of human mental reasoning, decision ma...

Evaluation of AI Summaries on Interdisciplinary Understanding of Ophthalmology Notes.

JAMA ophthalmology
IMPORTANCE: Specialized ophthalmology terminology limits comprehension for nonophthalmology clinicians and professionals, hindering interdisciplinary communication and patient care. The clinical implementation of large language models (LLMs) into pra...

A Concept for Integrating AI-Based Support Systems into Clinical Practice.

Studies in health technology and informatics
The integration of artificial intelligence (AI) algorithms into clinical practice holds immense potential to improve patient care, but widespread adoption still faces significant challenges, including interoperability issues. We propose a concept for...

Next-Generation Teleophthalmology: AI-enabled Quality Assessment Aiding Remote Smartphone-based Consultation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Blindness and other eye diseases are a global health concern, particularly in low- and middle-income countries like India. In this regard, during the COVID-19 pandemic, teleophthalmology became a lifeline, and the Grabi attachment for smartphone-base...

[Challenges and prospects in the application of artificial intelligence for ocular disease screening and diagnosis].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
In recent years, artificial intelligence (AI) technologies have experienced substantial growth across various sectors, with significant strides made particularly in medical AI through advancements such as large models. The application of AI within th...

A Clinician's Guide to Sharing Data for AI in Ophthalmology.

Investigative ophthalmology & visual science
Data is the cornerstone of using AI models, because their performance directly depends on the diversity, quantity, and quality of the data used for training. Using AI presents unique potential, particularly in medical applications that involve rich d...