Evaluating the diagnostic reasoning of large language models in complex neuro-ophthalmological cases: a comparative analysis of GPT-o1 Pro, GPT-4o, Gemini, Grok 2 and DeepSeek
The study underscores the superior clinical reasoning capabilities of ChatGPT-o1 Pro in neuro-ophthalmology compared with other LLMs, highlighting its potential for enhancing diagnostic processes in this complex field.
Authors
- Ling‐Ping Cen (ORCID: https://orcid.org/0000-0003-3876-0606)
- Xiaoxue He (ORCID: https://orcid.org/0000-0003-1920-8672)
- Yudong Chen (ORCID: https://orcid.org/0000-0002-3034-4651)
- Biyue Guo (ORCID: https://orcid.org/0000-0001-6282-8143)
- Yih Chung Tham (ORCID: https://orcid.org/0000-0002-6752-797X)
- Yun Wang (ORCID: https://orcid.org/0000-0002-8238-5367)
- Jinghui Liang (ORCID: https://orcid.org/0009-0007-7899-9781)
- Zibo Liu (ORCID: https://orcid.org/0000-0001-8970-2823)
- Fang-Fang Zhao
- Hu Zhan-chi
Institutions
- Hong Kong Polytechnic University (HK)
- Johns Hopkins University (US)
- National University of Singapore (SG)
- Guangdong Medical College (CN)
- Chinese University of Hong Kong (HK)
- Shantou University (CN)
- Singapore Eye Research Institute (SG)
Publication Details
- Journal
- BMJ Open Ophthalmology
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1136/bmjophth-2025-002185
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province