ArticleGraefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie2023
Artificial intelligence-based ChatGPT chatbot responses for patient and parent questions on vernal keratoconjunctivitis.
Article in Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses 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
33 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Evaluating Large Language Models in Ophthalmology: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Large Language Models for Chatbot Health Advice Studies: A Systematic Review.JAMA network open · 2025Pooled it
- Evaluating the role of ChatGPT in patient questions regarding drug allergies.The World Allergy Organization journal · 2026Article
- Bilingual evaluation of large language models for patient education in refractive surgery.International journal of ophthalmology · 2026Article
- Large Language Model-Generated Patient Education Materials in Pediatric Ophthalmology: A Scoping Review.Clinical ophthalmology (Auckland, N.Z.) · 2026Review
- Comparative performance analysis of global and chinese-domain large language models for myopia.Eye (London, England) · 2025Article
- Article
- Evaluating the Efficacy of Artificial Intelligence-Driven Chatbots in Addressing Queries on Vernal Conjunctivitis.Cureus · 2025Article
- Exploring the performance of large language models on hepatitis B infection-related questions: A comparative study.World journal of gastroenterology · 2025Article
- Generative AI/LLMs for Plain Language Medical Information for Patients, Caregivers and General Public: Opportunities, Risks and Ethics.Patient preference and adherence · 2025Review
- Enhancing treatment decision-making for low back pain: a novel framework integrating large language models with retrieval-augmented generation technology.Frontiers in medicine · 2025Article
- Enhancing patient-centered information on implant dentistry through prompt engineering: a comparison of four large language models.Frontiers in oral health · 2025Article
- Opportunities and Challenges of Chatbots in Ophthalmology: A Narrative Review.Journal of personalized medicine · 2024Review
- High accuracy but limited readability of large language model-generated responses to frequently asked questions about Kienböck's disease.BMC musculoskeletal disorders · 2024Article
- Exploring the Potential of Code-Free Custom GPTs in Ophthalmology: An Early Analysis of GPT Store and User-Creator Guidance.Ophthalmology and therapy · 2024Article
- Utilizing Large Language Models in Ophthalmology: The Current Landscape and Challenges.Ophthalmology and therapy · 2024Review
- Development and evaluation of a large language model of ophthalmology in Chinese.The British journal of ophthalmology · 2024Article
- Comparing generative and retrieval-based chatbots in answering patient questions regarding age-related macular degeneration and diabetic retinopathy.The British journal of ophthalmology · 2024Article
- Article
- Assessing Generative Pretrained Transformers (GPT) in Clinical Decision-Making: Comparative Analysis of GPT-3.5 and GPT-4.Journal of medical Internet research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
37129631What 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.