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The imitation game: large language models versus multidisciplinary tumor boards: benchmarking AI against 21 sarcoma centers from the ring trial

The study aims to compare the treatment recommendations generated by four leading large language models (LLMs) with those from 21 sarcoma centers’ multidisciplinary tumor boards (MTBs) of the sarcoma ring trial in managing complex soft tissue sarcoma (STS) cases.

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Bibliographic Details
Main Authors: Li, Cheng-Peng (Author) , Kalisa, Aimé Terence (Author) , Roohani, Siyer (Author) , Hummedah, Kamal (Author) , Menge, Franka (Author) , Reißfelder, Christoph (Author) , Albertsmeier, Markus (Author) , Kasper, Bernd (Author) , Jakob, Jens (Author) , Yang, Cui (Author)
Format: Article (Journal)
Language:English
Published: 10 September 2025
In: Journal of cancer research and clinical oncology
Year: 2025, Volume: 151, Issue: 9, Pages: 1-15
ISSN:1432-1335
DOI:10.1007/s00432-025-06304-9
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1007/s00432-025-06304-9
Verlag, kostenfrei, Volltext: https://link.springer.com/article/10.1007/s00432-025-06304-9
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Author Notes:Cheng-Peng Li, Aimé Terence Kalisa, Siyer Roohani, Kamal Hummedah, Franka Menge, Christoph Reißfelder, Markus Albertsmeier, Bernd Kasper, Jens Jakob, Cui Yang
Description
Summary:The study aims to compare the treatment recommendations generated by four leading large language models (LLMs) with those from 21 sarcoma centers’ multidisciplinary tumor boards (MTBs) of the sarcoma ring trial in managing complex soft tissue sarcoma (STS) cases.
Item Description:Gesehen am 17.11.2025
Physical Description:Online Resource
ISSN:1432-1335
DOI:10.1007/s00432-025-06304-9

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