Expert-guided large language models for clinical decision support in precision oncology
PURPOSE: Rapidly expanding medical literature challenges oncologists seeking targeted cancer - therapies. General-purpose large language models (LLMs) lack domain-specific knowledge, - limiting their clinical utility. This study introduces the LLM system ...
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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
October 30, 2024
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| In: |
JCO precision oncology
Year: 2024, Volume: 8, Pages: 1-14 |
| ISSN: | 2473-4284 |
| DOI: | 10.1200/PO-24-00478 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1200/PO-24-00478 Verlag, kostenfrei, Volltext: https://ascopubs.org/doi/10.1200/PO-24-00478 |
| Author Notes: | Jacqueline Lammert, Tobias Dreyer, Sonja Mathes, Leonid Kuligin, Kai J. Borm, Ulrich A. Schatz, Marion Kiechle, Alisa M. Lörsch, Johannes Jung, Sebastian Lange, Nicole Pfarr, Anna Durner, Kristina Schwamborn, Christof Winter, Dyke Ferber, Jakob Nikolas Kather, Carolin Mogler, Anna L. Illert, Maximilian Tschochohei |
| Summary: | PURPOSE: Rapidly expanding medical literature challenges oncologists seeking targeted cancer - therapies. General-purpose large language models (LLMs) lack domain-specific knowledge, - limiting their clinical utility. This study introduces the LLM system ... |
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| Item Description: | Gesehen am 28.11.2025 |
| Physical Description: | Online Resource |
| ISSN: | 2473-4284 |
| DOI: | 10.1200/PO-24-00478 |