ArticleEye (London, England)2024
A side-by-side evaluation of Llama 2 by meta with ChatGPT and its application in ophthalmology.
Article in Eye (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ophthalmic Image Synthesis and Analysis with Generative Adversarial Network Artificial Intelligence.Journal of imaging informatics in medicine · 2026Pooled it
- Assessment of artificial intelligence chatbots in responding to dental occlusion questions: a comparative study.BMC oral health · 2025Article
- OpenAI's Sora in medical education: artificial videos in the classroom of the future Sora d'OpenAI dans l'enseignement médical : des vidéos artificielles dans la salle de classe du futur.Canadian medical education journal · 2025Article
- A large language model digital patient system enhances ophthalmology history taking skills.NPJ digital medicine · 2025Article
- Comparative evaluation of ChatGPT and LLaMA for reliability, quality, and accuracy in familial Mediterranean fever.European journal of pediatrics · 2025Article
- AI-driven personalized nutrition: RAG-based digital health solution for obesity and type 2 diabetes.PLOS digital health · 2025Article
- Relation extraction using large language models: a case study on acupuncture point locations.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Applications of ChatGPT in the diagnosis, management, education, and research of retinal diseases: a scoping review.International journal of retina and vitreous · 2024Article
- FFA-GPT: an automated pipeline for fundus fluorescein angiography interpretation and question-answer.NPJ digital medicine · 2024Article
- Trustworthy AI in Telehealth: Navigating Challenges, Ethical Considerations, and Future Opportunities for Equitable Healthcare Delivery.Healthcare technology lettersReview
- Large Language Models in Ophthalmology: A Review of Publications from Top Ophthalmology Journals.Ophthalmology scienceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.