| Autor: |
Hitoshi Tabuchi, Isana Nakajima, Mhairi Day, Tsuyoshi Yoneda, Mao Tanabe, Niall Strang, Justin Engelmann, Hodaka Deguchi, Masahiro Akada, Takaaki Moriguchi, Yuta Nakaniida, Hideki Tsuji |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2045-2322 |
| DOI: |
10.1038/s41598-024-80732-4 |
| Popis: |
Abstract Sebaceous carcinoma is difficult to distinguish from chalazion due to their rarity and clinicians’ limited experience. This study investigated the potential of AI-generated image training to improve diagnostic skills for these eyelid tumors compared to traditional video lecture-based education. Students from Orthoptics, Optometry, and Vision Research (n = 55) were randomly assigned to either an AI-generated image training group or a traditional video lecture group. Diagnostic performance was assessed using a 50-image quiz before and after the intervention. Both groups showed significant improvement in overall diagnostic accuracy (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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