ArticleOphthalmology science
Can OpenAI's New o1 Model Outperform Its Predecessors in Common Eye Care Queries?
Article in Ophthalmology science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Comparison of the performance of large language models in answering patient questions related to cataract.iScience · 2026Article
- BEnchmarking Large Language Models for Ophthalmology (BELO): An Expert-Curated Data Set and Evaluation Framework for Knowledge and Reasoning.Ophthalmology science · 2026Article
- Evolving Consultation: Enhancing Ophthalmic Diagnostic Performance Using Large Language Model.Ophthalmology science · 2026Article
- Re: Pushpanathan et al.: Can OpenAI's New o1 Model Outperform Its Predecessors in Common Eye Care Queries?Ophthalmology science · 2026Article
- Reply.Ophthalmology science · 2026Article
- Ophthalmological Question Answering and Reasoning Using OpenAI o1 vs Other Large Language Models.JAMA ophthalmology · 2025Article
- Performance of ChatGPT-4 Omni and Gemini 1.5 Pro on Ophthalmology-Related Questions in the Turkish Medical Specialty Exam.Turkish journal of ophthalmology · 2025Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The newly launched OpenAI o1 is said to offer improved reasoning, potentially providing higher quality responses to eye care queries. However, its performance remains unassessed. We evaluated the performance of o1, ChatGPT-4o, and ChatGPT-4 in addressing ophthalmic-related queries, focusing on correctness, completeness, and readability. Design: Cross-sectional study. Subjects: Sixteen queries, previously identified as suboptimally responded to by ChatGPT-4 from prior studies, were used, covering 3 subtopics: myopia (6 questions), ocular symptoms (4 questions), and retinal conditions (6 questions). Methods: For each subtopic, 3 attending-level ophthalmologists, masked to the model sources, evaluated the responses based on correctness, completeness, and readability (on a 5-point scale for each metric). Main Outcome Measures: Mean summed scores of each model for correctness, completeness, and readability, rated on a 5-point scale (maximum score: 15). Results: O1 scored highest in correctness (12.6) and readability (14.2), outperforming ChatGPT-4, which scored 10.3 ( Conclusions: While o1 is marketed as offering improved reasoning capabilities, its performance in addressing eye care queries does not significantly differ from its predecessor, ChatGPT-4o. Nevertheless, it surpasses ChatGPT-4, particularly in correctness and readability. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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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.