Attitudes toward large language model-based Artificial Intelligence systems as an information source for shared decision-making in radiation oncology.
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| Title: | Attitudes toward large language model-based Artificial Intelligence systems as an information source for shared decision-making in radiation oncology. |
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| Authors: | Moser R; Department of Radiation Oncology, TUM University Hospital, Klinikum Rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich 81675, Germany., Buchecker LM; Department of Radiation Oncology, TUM University Hospital, Klinikum Rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich 81675, Germany., Nano J; Department of Radiation Oncology, TUM University Hospital, Klinikum Rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich 81675, Germany., Mayr NA; College of Human Medicine, Michigan State University, East Lansing, MI 4882, United States., Behzadi ST; Department of Radiation Oncology, TUM University Hospital, Klinikum Rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich 81675, Germany., Kiesl S; Department of Radiation Oncology, TUM University Hospital, Klinikum Rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich 81675, Germany., Maier S; Department of Radiation Oncology, TUM University Hospital, Klinikum Rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich 81675, Germany., Allwohn L; Department of Radiation Oncology, TUM University Hospital, Klinikum Rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich 81675, Germany., Lammert J; Department of Gynecology and Center for Hereditary Breast and Ovarian Cancer, Technical University of Munich (TUM), School of Medicine and Health, Klinikum rechts der Isar, TUM University Hospital, Munich 81675, Germany.; Institute of Artificial Intelligence and Informatics in Medicine (AIIM), TUM University Hospital, Technical University of Munich (TUM), Munich 81675, Germany.; German Cancer Consortium (DKTK), partner site Munich, a partnership between DKFZ and TUM University Hospital, Munich, 81675, Germany., Adams LC; Department of Diagnostic and Interventional Radiology, School of Medicine and Health, Klinikum rechts der Isar, TUM University Hospital, Technical University of Munich, Munich 81675, Germany., Tschochohei M; Institute of Artificial Intelligence and Informatics in Medicine (AIIM), TUM University Hospital, Technical University of Munich (TUM), Munich 81675, Germany.; Google Deutschland GmbH, Munich 80636, Germany., Combs SE; Department of Radiation Oncology, TUM University Hospital, Klinikum Rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich 81675, Germany.; German Cancer Consortium (DKTK), partner site Munich, a partnership between DKFZ and TUM University Hospital, Munich, 81675, Germany.; Institute of Innovative Radiotherapy (iRT), Department of Radiation Sciences (DRS), Helmholtz Zentrum München, Oberschleißheim 85764, Germany., Borm KJ; Department of Radiation Oncology, TUM University Hospital, Klinikum Rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich 81675, Germany.; Bavarian Center for Cancer Research (BZKF), Technical University Munich, Munich 81675, Germany. |
| Source: | The oncologist [Oncologist] 2026 Jan 17; Vol. 31 (2). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9607837 Publication Model: Print Cited Medium: Internet ISSN: 1549-490X (Electronic) Linking ISSN: 10837159 NLM ISO Abbreviation: Oncologist Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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