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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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Bibliographische Detailangaben
Hauptverfasser: Li, Cheng-Peng (VerfasserIn) , Kalisa, Aimé Terence (VerfasserIn) , Roohani, Siyer (VerfasserIn) , Hummedah, Kamal (VerfasserIn) , Menge, Franka (VerfasserIn) , Reißfelder, Christoph (VerfasserIn) , Albertsmeier, Markus (VerfasserIn) , Kasper, Bernd (VerfasserIn) , Jakob, Jens (VerfasserIn) , Yang, Cui (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 10 September 2025
In: Journal of cancer research and clinical oncology
Year: 2025, Jahrgang: 151, Heft: 9, Pages: 1-15
ISSN:1432-1335
DOI:10.1007/s00432-025-06304-9
Online-Zugang: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
Volltext
Verfasserangaben:Cheng-Peng Li, Aimé Terence Kalisa, Siyer Roohani, Kamal Hummedah, Franka Menge, Christoph Reißfelder, Markus Albertsmeier, Bernd Kasper, Jens Jakob, Cui Yang
Beschreibung
Zusammenfassung: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.
Beschreibung:Gesehen am 17.11.2025
Beschreibung:Online Resource
ISSN:1432-1335
DOI:10.1007/s00432-025-06304-9

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