Predicting molecular types of adult-type diffuse gliomas based on MRI reports with large language models.
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| Title: | Predicting molecular types of adult-type diffuse gliomas based on MRI reports with large language models. |
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| Authors: | Suh PS; Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea., Lee D; Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea., Bang CB; Department of Psychiatry, Yonsei University College of Medicine, Seoul, Korea.; Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Korea., Han K; Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea., Choi KS; Department of Radiology, Seoul National University Hospital, Seoul, Korea., Kim M; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Seoul, Korea., Park JE; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Seoul, Korea., Shin NY; Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea., Ahn SS; Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea., Choi SH; Department of Radiology, Seoul National University Hospital, Seoul, Korea., Kim HS; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Seoul, Korea., Lee SK; Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea., Chang JH; Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea., Kim SH; Department of Pathology, Yonsei University College of Medicine, Seoul, Korea., Foltyn-Dumitru M; Division for Computational Radiology & Clinical AI (CCIBonn.ai), Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany.; Medical Faculty Bonn, University of Bonn, Bonn, Germany., You SC; Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea., Vollmuth P; Division for Computational Radiology & Clinical AI (CCIBonn.ai), Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany.; Medical Faculty Bonn, University of Bonn, Bonn, Germany.; Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany., Kim BH; Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea. egyptdj@yuhs.ac.; Department of Psychiatry, Yonsei University College of Medicine, Seoul, Korea. egyptdj@yuhs.ac.; Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Korea. egyptdj@yuhs.ac., Park YW; Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea. yaewonpark@yuhs.ac. |
| Source: | European radiology [Eur Radiol] 2026 May; Vol. 36 (5), pp. 3743-3754. Date of Electronic Publication: 2025 Dec 22. |
| Publication Type: | Journal Article; Multicenter Study |
| Journal Info: | Publisher: Springer International Country of Publication: Germany NLM ID: 9114774 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1084 (Electronic) Linking ISSN: 09387994 NLM ISO Abbreviation: Eur Radiol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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