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Collaborative framework on responsible AI in LLM-driven CDSS for precision oncology leveraging real-world patient data
0
Zitationen
17
Autoren
2025
Jahr
Abstract
Precision oncology leverages real-world data, essential for identifying biomarkers and therapies. Large language models (LLMs) can aid at structuring unstructured data, overcoming current bottlenecks in precision oncology. We propose a framework for responsible LLM integration into precision oncology, co-developed by multidisciplinary experts and supported by Cancer Core Europe. Five thematic dimensions and ten principles for practice are outlined and illustrated through application to uterine carcinosarcoma in a thought experiment.
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Autoren
Institutionen
- Johannes Gutenberg University Mainz(DE)
- University Medical Center of the Johannes Gutenberg University Mainz(DE)
- Technical University of Munich(DE)
- Heidelberg University(DE)
- University Hospital Heidelberg(DE)
- Fresenius (Germany)(DE)
- National Center for Tumor Diseases(DE)
- Helmholtz Zentrum München(DE)
- Radboud University Nijmegen(NL)
- Radboud University Medical Center(NL)
- The Netherlands Cancer Institute(NL)
- Institut Gustave Roussy(FR)
- German Cancer Research Center(DE)
- Vall d'Hebron Institute of Oncology(ES)
- Fondazione IRCCS Istituto Nazionale dei Tumori(IT)
- Karolinska University Hospital(SE)
- Karolinska Institutet(SE)
- Cancer Research UK Cambridge Center(GB)