AIMC Topic: Ophthalmology

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A Review of Recent Developments in Artificial Intelligence and Big Data Technologies for Ophthalmology Referrals and Clinical Practice.

Medical science monitor : international medical journal of experimental and clinical research
Ophthalmology is undergoing rapid transformation through the integration of smart technologies such as artificial intelligence (AI), big data analytics, and clinical decision support systems (CDSS). With increasing pressure to improve clinical effici...

Neural network for natural language processing to determine treatment urgency in an ophthalmology emergency department.

The British journal of ophthalmology
BACKGROUND: In an ophthalmology emergency department, determining treatment urgency is crucial for patient safety and the efficient use of resources. The aim of this study was to use artificial intelligence to develop a neural network and evaluate it...

Assessing the quality and educational applicability of AI-generated anterior segment images in ophthalmology.

Scientific reports
Text-to-image (T2I) artificial intelligence models are being increasingly explored in medical education, yet their utility in ophthalmology remains unclear. Slit-lamp anterior segment photography, as a cornerstone of ophthalmic training, provides an ...

Real-world data landscape for glaucoma in Europe: a questionnaire-based analysis of resources among European Glaucoma Society members.

BMJ open ophthalmology
BACKGROUND/AIMS: To investigate the landscape to support Europe-wide collaborative real-world data (RWD) collection, exploring whether required resources are available to glaucoma clinicians.

Generative AI in medical education: feasibility and educational value of LLM-generated clinical cases with MCQs.

BMC medical education
OBJECTIVE: To evaluate the feasibility and educational value of employing large language models (LLMs) to generate clinical case scenario with multiple-choice questions (MCQs) for undergraduate medical education.

Evaluating Large Language Models in Ophthalmology: Systematic Review.

Journal of medical Internet research
BACKGROUND: Large language models (LLMs) have the potential to revolutionize ophthalmic care, but their evaluation practice remains fragmented. A systematic assessment is crucial to identify gaps and guide future evaluation practices and clinical int...

Evaluating the quality of ChatGPT-generated medical information on major ophthalmic conditions: A comparative assessment against the EQIP tool and guidelines.

PloS one
BACKGROUND: The use of artificial intelligence for creating medical information is on the rise. Nonetheless, the accuracy and reliability of such information require thorough assessment. As a language model capable of generating text, ChatGPT needs a...

Ocular implants and inserts: revolutionizing drug delivery in ophthalmology.

International journal of pharmaceutics
The ophthalmic route for drug administration remains a significant constraint in ophthalmology due to the unique anatomy and several protective barriers in the eyes, which limit absorption and therapeutic efficacy. Conventionally, drugs are delivered...

Artificial intelligence-generated informed patient consent in various ophthalmological procedures: A comparative study of correctness, completeness, readability, and real-word application between Deepseek and Chatgpt 4o.

Indian journal of ophthalmology
PURPOSE: To study the correctness, completeness, language and readability, and real-world applicability of artificial intelligence chatbots-generated informed consent forms for various ophthalmological procedures and interventions.

Identifying Transportation Needs in Ophthalmology Clinic Notes Using Natural Language Processing: Retrospective, Cross-Sectional Study.

JMIR medical informatics
BACKGROUND: Transportation insecurity is a known barrier to accessing eye care and is associated with poorer visual outcomes for patients. However, its mention is seldom captured in structured data fields in electronic health records, limiting effort...