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Radiomics enhance the prediction of endovascular treatment success for femoropopliteal chronic total occlusions: a proof-of-concept study.

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第一作者: Konstantinos,Vrettos
第一单位: Artificial Intelligence and Translational Imaging (ATI) Lab, Department of Radiology, School of Medicine, University of Crete, Heraklion, Greece.
作者单位: Artificial Intelligence and Translational Imaging (ATI) Lab, Department of Radiology, School of Medicine, University of Crete, Heraklion, Greece. [1] Department of Medical Imaging, University Hospital of Heraklion, Heraklion, Crete, Greece. [2] Department of Radiology, School of Medicine, University of Crete, Heraklion, Greece; Interventional Radiology Interventional Radiology Unit, Department of Medical Imaging, University Hospital of Heraklion, Greece. [3] Vascular Surgery Unit, Department of Cardiothoracic and Vascular Surgery, University Hospital of Heraklion, University of Crete, Heraklion, Greece. [4] Department of Radiology, School of Medicine, University of Crete, Heraklion, Greece; Interventional Radiology Interventional Radiology Unit, Department of Medical Imaging, University Hospital of Heraklion, Greece. Electronic address: nikolas_mat@hotmail.com. [5] Artificial Intelligence and Translational Imaging (ATI) Lab, Department of Radiology, School of Medicine, University of Crete, Heraklion, Greece; Department of Medical Imaging, University Hospital of Heraklion, Heraklion, Crete, Greece; Computational Biomedicine Lab, Institute of Computer Science Foundation for Research and Technology Hellas (ICS-FORTH), Heraklion, Crete, Greece; Division of Radiology, Department of Clinical Science Intervention and Technology (CLINTEC), Karolinska Institute, Huddinge, Sweden. Electronic address: miklontzas@uoc.gr. [6]
DOI 10.1016/j.ejrad.2025.112496
PMID 41166916
发布时间 2025-12-01
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European journal of radiology

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