aceEvaluation and Comparison of Large Language Models in Answering Frequently Asked Patient Questions on Glaucoma
Prcis: ChatGPT-o1 and DeepSeek-R1 demonstrated similar performance in answering frequently asked patient questions. However, limitations in reliability and high reading levels underscore the need for greater oversight and refinement to improve their role in patient education. Purpose: This study evaluated and compared the reliability and readability of responses generated by ChatGPT-o1 and DeepSeek-R1 to frequently asked patient questions (FAQs) on glaucoma. The findings aim to elucidate the utility of each mode…
ChatGPT-o1 and DeepSeek-R1 gave glaucoma patient answers with notable accuracy errors, including false claims about tunnel vision and unsubstantiated lifestyle advice, written at 8th-12th grade reading levels.
The study evaluated only the first 10 Google People Also Ask questions and two chatbot models, which limits how broadly the results apply.
Evidence
- Peer-reviewedJournal of Glaucoma2026-10-12
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Truvace Impact Record TRV-2026-1380, v1: “Evaluation and Comparison of Large Language Models in Answering Frequently Asked Patient Questions on Glaucoma.” Truvace, 2026-10-14. /record/TRV-2026-1380 (accessed at citation time). sha256 0ded77124b3cfa53…
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