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Lead strangulation is a dangerous complication of epicardial pacemaker insertion. This complication has been increasingly highlighted lately. Our institution has recently identified four cases over the past five years.

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Background Orthodontic diagnostic workflows often rely on manual classification and archiving of large volumes of patient images, a process that is both time-consuming and prone to errors such as mislabeling and incomplete documentation. These challenges can compromise treatment accuracy and overall patient care. To address these issues, we propose an artificial intelligence (AI)-driven deep learning framework based on convolutional neural networks (CNNs) to automate the classification and archiving of orthodontic diagnostic images.

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Comparison of dark-field chest radiography and CT for the assessment of COVID-19 pneumonia.

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Department of Diagnostic and Interventional Radiology, School of Medicine & Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.

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