The performance of artificial intelligence on a national medical licensing examination: the answers of large language models to text questions : research letter: medicine
Significant advances are being made in the development of large language models (LLM) for use in the field of clinical medicine. LLM are now able to pass major medical exams such as the United States Medical Licensing Examination (USMLE) and two...
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| Hauptverfasser: | , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
27 December 2024
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| In: |
Deutsches Ärzteblatt
Year: 2024, Jahrgang: 121, Heft: 26, Pages: 888-889 |
| ISSN: | 1866-0452 |
| DOI: | 10.3238/arztebl.m2024.0231 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.3238/arztebl.m2024.0231 Verlag, kostenfrei, Volltext: https://www.aerzteblatt.de/int/archive/article?id=242258 |
| Verfasserangaben: | Mark Enrik Geissler, Merle Goeben, Kira A. Glasmacher, Jean-Paul Bereuter, Rona Berit Geissler, Isabella C. Wiest, Fiona R. Kolbinger, Jakob Nikolas Kather |
| Zusammenfassung: | Significant advances are being made in the development of large language models (LLM) for use in the field of clinical medicine. LLM are now able to pass major medical exams such as the United States Medical Licensing Examination (USMLE) and two... |
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| Beschreibung: | Gesehen am 08.04.2025 |
| Beschreibung: | Online Resource |
| ISSN: | 1866-0452 |
| DOI: | 10.3238/arztebl.m2024.0231 |