TY  - JOUR
AU  - Carl, Nicolas
AU  - Haggenmüller, Sarah
AU  - Wies, Christoph
AU  - Nguyen, Lisa
AU  - Winterstein, Jana Theres
AU  - Hetz, Martin Joachim
AU  - Mangold, Maurin Helen
AU  - Hartung, Friedrich Otto
AU  - Grüne, Britta
AU  - Holland-Letz, Tim
AU  - Michel, Maurice Stephan
AU  - Brinker, Titus
AU  - Wessels, Frederik
TI  - Evaluating interactions of patients with large language models for medical information.
JO  - BJU international
VL  - 135
IS  - 6
SN  - 1464-4096
CY  - Oxford
PB  - Wiley-Blackwell
M1  - DKFZ-2025-00392
SP  - 1010-1017
PY  - 2025
N1  - #EA:C140#LA:C140# / 2025 Jun;135(6):1010-1017
AB  - To explore the interaction of real-world patients with a chatbot in a clinical setting, investigating key aspects of medical information provided by large language models (LLMs).The study enrolled 300 patients seeking urological counselling between February and July 2024. First, participants voluntarily conversed with a Generative Pre-trained Transformer 4 (GPT-4) powered chatbot to ask questions related to their medical situation. In the following survey, patients rated the perceived utility, completeness, and understandability of the information provided during the simulated conversation as well as user-friendliness. Finally, patients were asked which, in their experience, best answered their questions: LLMs, urologists, or search engines.A total of 292 patients completed the study. The majority of patients perceived the chatbot as providing useful, complete, and understandable information, as well as being user-friendly. However, the ability of human urologists to answer medical questions in an understandable way was rated higher than of LLMs. Interestingly, 53
KW  - artificial intelligence (Other)
KW  - clinical trial (Other)
KW  - implementation science (Other)
KW  - large language models (Other)
KW  - patient interaction (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:39967059
DO  - DOI:10.1111/bju.16676
UR  - https://inrepo02.dkfz.de/record/298963
ER  -