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DeepSeek-R1 vs OpenAI o1 for Ophthalmic Diagnoses and Management Plans
2
Zitationen
11
Autoren
2025
Jahr
Abstract
DeepSeek-R1 outperformed OpenAI o1 in diagnosis and management across subspecialties while lowering operating costs, supporting the potential of open-weight, reinforcement learning-augmented LLMs as scalable and cost-saving tools for clinical decision support. Further investigations should evaluate safety guardrails and assess performance of self-hosted adaptations of DeepSeek-R1 with domain-specific ophthalmic expertise to optimize clinical utility.
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Autoren
Institutionen
- University of Toronto(CA)
- McGill University(CA)
- University of Waterloo(CA)
- Centre Hospitalier de l’Université de Montréal(CA)
- Hôpital Maisonneuve-Rosemont(CA)
- Université de Montréal(CA)
- Cleveland Clinic(US)
- Cleveland Eye Clinic(US)
- Doheny Eye Institute(US)
- Unity Health Toronto
- St. Michael's Hospital(CA)
- Moorfields Eye Hospital(GB)
- University College London(GB)
- Moorfields Eye Hospital NHS Foundation Trust(GB)