Direct image to subtype prediction for brain tumors using deep learning.
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| Title: | Direct image to subtype prediction for brain tumors using deep learning. |
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| Authors: | Hewitt KJ; Department of Medicine III, University Hospital RWTH Aachen, Aachen, North Rhine-Westphalia, Germany.; Clinical Artificial Intelligence, Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Saxony, Germany., Löffler CML; Department of Medicine III, University Hospital RWTH Aachen, Aachen, North Rhine-Westphalia, Germany.; Clinical Artificial Intelligence, Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Saxony, Germany.; Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Saxony, Germany., Muti HS; Clinical Artificial Intelligence, Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Saxony, Germany.; Department of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus Dresden, Dresden, Saxony, Germany., Berghoff AS; Department of Medicine 1, Division of Oncology, Medical University of Vienna, Vienna, Vienna, Austria., Eisenlöffel C; Department of Pathology, St. Georg Teaching Hospital, University of Leipzig, Leipzig, Saxony, Germany., van Treeck M; Clinical Artificial Intelligence, Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Saxony, Germany., Carrero ZI; Clinical Artificial Intelligence, Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Saxony, Germany., El Nahhas OSM; Clinical Artificial Intelligence, Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Saxony, Germany., Veldhuizen GP; Clinical Artificial Intelligence, Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Saxony, Germany., Weil S; Neurology Clinic, Department of Neurology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Baden- Württemberg, Germany.; Clinical Cooperation Unit Neuro-oncology, Department of Neurology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Baden- Württemberg, Germany., Saldanha OL; Department of Medicine III, University Hospital RWTH Aachen, Aachen, North Rhine-Westphalia, Germany., Bejan L; School of Medicine, Faculty of Medicine and Dentistry, University College London, London, Greater London, UK., Millner TO; Division of Neuropathology, Queen Square Institute of Neurology, University College London, London, Greater London, UK.; Blizard Institute, Faculty of Medicine and Dentistry, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, Greater London, UK., Brandner S; Division of Neuropathology, Queen Square Institute of Neurology, University College London, London, Greater London, UK., Brückmann S; Institut für Pathologie, University Hospital Carl Gustav Carus, Dresden, Saxony, Germany., Kather JN; Department of Medicine III, University Hospital RWTH Aachen, Aachen, North Rhine-Westphalia, Germany.; Clinical Artificial Intelligence, Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Saxony, Germany.; Department of Internal Medicine I, University Hospital Carl Gustav Carus, Dresden, Saxony, Germany.; Pathology & Data Analytics, Faculty of Medicine and Health, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, West Yorkshire, UK.; Department of Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Baden- Württemberg, Germany. |
| Source: | Neuro-oncology advances [Neurooncol Adv] 2023 Nov 01; Vol. 5 (1), pp. vdad139. Date of Electronic Publication: 2023 Nov 01 (Print Publication: 2023). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 101755003 Publication Model: eCollection Cited Medium: Internet ISSN: 2632-2498 (Electronic) Linking ISSN: 26322498 NLM ISO Abbreviation: Neurooncol Adv Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2632-2498 |
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| DOI: | 10.1093/noajnl/vdad139 |
