Superhuman performance in urology board questions by an explainable large language model enabled for context integration of the European Association of Urology guidelines: the UroBot study

Fuente: arXiv

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Bibliographic Details
Main Authors:	Hetz, Martin J., Carl, Nicolas, Haggenmüller, Sarah, Wies, Christoph, Michel, Maurice Stephan, Wessels, Frederik, Brinker, Titus J.
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2406.01428