DeepSeek: Another step forward in the diagnosis of oral lesions
Artificial intelligence (AI) is increasingly being explored as a tool for medical diagnosis, particularly in fields with limited specialized training, such as oral medicine. This study evaluates the performance of DeepSeek-R1, an open-source large language model (LLM), in diagnosing oral diseases and conditions using text-based case descriptions from the New England Journal of Medicine's "Image Challenge." Results indicate that DeepSeek-R1 achieved a diagnostic accuracy of 91.6 %, slightly outperforming ChatGPT-4o (88.9 %) and significantly exceeding the 47.8 % accuracy of the journal' readers. While DeepSeek lacks direct image interpretation capabilities, it demonstrates high proficiency in textual diagnostic tasks. These findings suggest that DeepSeek-R1 could be a valuable aid for medical professionals in diagnosing oral diseases.
Authors
- Pedro Diz Dios (ORCID: https://orcid.org/0000-0002-1483-401X)
- Márcio Diniz Freitas (ORCID: https://orcid.org/0000-0001-5349-1091)
Institutions
- Universidade de Santiago de Compostela (ES)
Publication Details
- Journal
- Journal of Dental Sciences
- Published
- 2025-03-09
- DOI
- https://doi.org/10.1016/j.jds.2025.02.023
- Citations
- 18
- Primary Topic
- Oral and Maxillofacial Pathology
- Type
- article
- Field-Weighted Citation Impact
- 32.23