ArticleDigital health
Patients with floaters: Answers from virtual assistants and large language models.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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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
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 12 citations in OpenAlex.
- Evaluating Large Language Models in Ophthalmology: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Comparison of the readability of ChatGPT and Bard in medical communication: a meta-analysis.BMC medical informatics and decision making · 2025Pooled it
- Large Language Models in Ophthalmology: A Bibliographic Analysis.Turkish journal of ophthalmology · 2026Article
- Large language models in ophthalmology: a scoping review on their utility for clinicians, researchers, patients, and educators.Eye (London, England) · 2025Article
- Comparative Analysis of LLMs in Dry Eye Syndrome Healthcare Information.Diagnostics (Basel, Switzerland) · 2025Article
- Assessment of Large Language Models in Cataract Care Information Provision: A Quantitative Comparison.Ophthalmology and therapy · 2025Article
- A Performance Evaluation of Large Language Models in Keratoconus: A Comparative Study of ChatGPT-3.5, ChatGPT-4.0, Gemini, Copilot, Chatsonic, and Perplexity.Journal of clinical medicine · 2024Article
- Applications of ChatGPT in the diagnosis, management, education, and research of retinal diseases: a scoping review.International journal of retina and vitreous · 2024Article
- Large language models in patient education: a scoping review of applications in medicine.Frontiers in medicine · 2024Article
- Large language models and eye education: A narrative review.Oman journal of ophthalmologyReview
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 at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: "Floaters," a common complaint among patients of all ages, was used as a query term because it affects 30% of all people searching for eye care. The American Academy of Ophthalmology website's "floaters" section was used as a source for questions and answers (www.aao.org). Floaters is a visual obstruction that moves with the movement of the eye. They can be associated with retinal detachment, which can lead to vision loss. With the advent of large language model (LLM) chatbots ChatGPT, Bard versus virtual assistants (VA), Google Assistant, and Alexa, we analyzed their responses to "floaters." Methods: Using AAO.org, "Public & Patients," and its related subsection, "EyeHealth A-Z": Floaters and Flashes link, we asked four questions: (1) What are floaters? (2) What are flashes? (3) Flashes and Migraines? (4) Floaters and Flashes Treatment? to ChatGPT, Bard, Google Assistant, and Alexa. The American Academy of Ophthalmology (AAO) keywords were identified if they were highlighted. The "Flesch-Kincaid Grade Level" formula approved by the U.S. Department of Education, was used to evaluate the reading comprehension level for the responses. Results: Of the chatbots and virtual assistants, Google Assistant is the only one that uses the term "ophthalmologist." There is no mention of the urgency or emergency nature of floaters. AAO.org shows a lower reading level vs the LLMs and VA ( Conclusion: Currently, ChatGPT, Bard, Google Assistant, and Alexa are similar. Factual information is present but all miss the urgency of the diagnosis of a retinal detachment. Translational relevance: Both the LLM and virtual assistants are free and our patients will use them to obtain "floaters" information. There may be errors of omission with ChatGPT and a lack of urgency to seek a physician's care.
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.