Focal choroidal excavation (FCE)-related choroidal neovascular membrane (CNV) in a child.

Purpose: To report the rare clinical, optical coherence tomography (OCT), and OCT-angiography findings of a visually significant choroidal neovascular membrane (CNV) in the setting of focal choroidal excavation (FCE) in a child.

Methods: Case report and literature review.

Results: A 9-year-old girl with FCE-related central CNV based on clinical findings and multimodal imaging.

Pediatric macular hole associated with vitreoretinal traction on epiretinal lesions - a case report and literature review.

Purpose: We describe a case of non-traumatic macular hole in a pediatric patient associated with numerous epiretinal lesions throughout the macula.

Methods: A healthy 9-year-old girl presented to retina clinic with several months of blurry vision in the right eye. Clinically, there was a full-thickness macular hole with serous detachment and white epiretinal tufts.

Trust your gut: Establishing confidence in gastrointestinal models - An overview of the state of the science and contexts of use.

The webinar series and workshop titled “Trust Your Gut: Establishing Confidence in Gastrointestinal Models – An Overview of the State of the Science and Contexts of Use” was co-organized by NICEATM, NIEHS, FDA, EPA, CPSC, DoD, and the Johns Hopkins Center for Alternatives to Animal Testing (CAAT) and hosted at the National Institutes of Health in Bethesda, MD, USA on October 11-12, 2023. New approach methods (NAMs) for assessing issues of gastrointestinal tract (GIT)- related toxicity offer promise in addressing some of the limitations associated with animal-based assessments. GIT NAMs vary in complexity, from two-dimensional monolayer cell line-based systems to sophisticated 3-dimensional organoid systems derived from human primary cells.

A Comparative Study of Responses to Retina Questions from Either Experts, Expert-Edited Large Language Models, or Expert-Edited Large Language Models Alone.

Objective: To assess the quality, empathy, and safety of expert edited large language model (LLM), human expert created, and LLM responses to common retina patient questions.

Design: Randomized, masked multicenter study.

Participants: Twenty-one common retina patient questions were randomly assigned among 13 retina specialists.

Appropriateness of Ophthalmology Recommendations From an Online Chat-Based Artificial Intelligence Model.

Objective: To determine the appropriateness of ophthalmology recommendations from an online chat-based artificial intelligence model to ophthalmology questions.

Patients And Methods: Cross-sectional qualitative study from April 1, 2023, to April 30, 2023. A total of 192 questions were generated spanning all ophthalmic subspecialties.