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Titel:

Evaluation and mitigation of the limitations of large language models in clinical decision-making.

Dokumenttyp:
Journal Article
Autor(en):
Hager, Paul; Jungmann, Friederike; Holland, Robbie; Bhagat, Kunal; Hubrecht, Inga; Knauer, Manuel; Vielhauer, Jakob; Makowski, Marcus; Braren, Rickmer; Kaissis, Georgios; Rueckert, Daniel
Abstract:
Clinical decision-making is one of the most impactful parts of a physician's responsibilities and stands to benefit greatly from artificial intelligence solutions and large language models (LLMs) in particular. However, while LLMs have achieved excellent performance on medical licensing exams, these tests fail to assess many skills necessary for deployment in a realistic clinical decision-making environment, including gathering information, adhering to guidelines, and integrating into clinical w...     »
Zeitschriftentitel:
Nat Med
Jahr:
2024
Band / Volume:
30
Heft / Issue:
9
Seitenangaben Beitrag:
2613-2622
Volltext / DOI:
doi:10.1038/s41591-024-03097-1
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/38965432
Print-ISSN:
1078-8956
TUM Einrichtung:
Institut für Diagnostische und Interventionelle Radiologie (Prof. Makowski); Institut für KI und Informatik in der Medizin (Prof. Rückert)
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