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Performance of DeepSeek-R1 in ophthalmology: an evaluation of clinical decision-making and cost-effectiveness
15
Zitationen
13
Autoren
2025
Jahr
Abstract
DeepSeek-R1 shows strong diagnostic and management performance comparable to OpenAI o1 across ophthalmic subspecialties, while significantly reducing costs. These results support its use as a cost-effective, open-weight alternative to proprietary models.
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Autoren
Institutionen
- University of Toronto(CA)
- University of Ottawa(CA)
- McGill University(CA)
- University of Waterloo(CA)
- Université de Montréal(CA)
- Hôpital Maisonneuve-Rosemont(CA)
- Centre Hospitalier de l’Université de Montréal(CA)
- Cleveland Clinic(US)
- Cleveland Eye Clinic(US)
- St. Michael's Hospital(CA)
- Unity Health Toronto
- Doheny Eye Institute(US)
- Vita-Salute San Raffaele University(IT)
- Moorfields Eye Hospital NHS Foundation Trust(GB)
- University College London(GB)