Multimodal graph attention network for COVID-19 outcome prediction von Keicher, Matthias, Burwinkel, Hendrik, Bani-Harouni, David, Paschali, Magdalini, Czempiel, Tobias, Burian, Egon, Makowski, Marcus R., Braren, Rickmer, Navab, Nassir, Wendler, Thomas

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Identifying high school risk factors that forecast heavy drinking onset in understudied young adults von Zhao, Qingyu, Paschali, Magdalini, Dehoney, Joseph, Baker, Fiona C., de Zambotti, Massimiliano, De Bellis, Michael D., Goldston, David B., Nooner, Kate B., Clark, Duncan B., Luna, Beatriz, Nagel, Bonnie J., Brown, Sandra A., Tapert, Susan F., Eberson, Sonja, Thompson, Wesley K., Pfefferbaum, Adolf, Sullivan, Edith V., Pohl, Kilian M.

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Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT scans von Foo, Michelle Xiao-Lin, Kim, Seong Tae, Paschali, Magdalini, Goli, Leili, Burian, Egon, Makowski, Marcus, Braren, Rickmer, Navab, Nassir, Wendler, Thomas

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TeCNO: Surgical Phase Recognition with Multi-stage Temporal Convolutional Networks von Czempiel, Tobias, Paschali, Magdalini, Keicher, Matthias, Simson, Walter, Feussner, Hubertus, Kim, Seong Tae, Navab, Nassir

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Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning von Simson, Walter A, Paschali, Magdalini, Sideri-Lampretsa, Vasiliki, Navab, Nassir, Dahl, Jeremy J

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Generalizability vs. Robustness: Investigating Medical Imaging Networks Using Adversarial Examples von Paschali, Magdalini, Conjeti, Sailesh, Navarro, Fernando, Navab, Nassir

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Multi‐domain predictors of grip strength differentiate individuals with and without alcohol use disorder von Paschali, Magdalini, Zhao, Qingyu, Sassoon, Stephanie A., Pfefferbaum, Adolf, Sullivan, Edith V., Pohl, Kilian M.

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Confidence-Based Out-of-Distribution Detection: A Comparative Study and Analysis von Berger, Christoph, Paschali, Magdalini, Glocker, Ben, Kamnitsas, Konstantinos

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OperA: Attention-Regularized Transformers for Surgical Phase Recognition von Czempiel, Tobias, Paschali, Magdalini, Ostler, Daniel, Kim, Seong Tae, Busam, Benjamin, Navab, Nassir

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Detecting negative valence symptoms in adolescents based on longitudinal self-reports and behavioral assessments von Paschali, Magdalini, Kiss, Orsolya, Zhao, Qingyu, Adeli, Ehsan, Podhajsky, Simon, Müller-Oehring, Eva M., Gotlib, Ian H., Pohl, Kilian M., Baker, Fiona C.

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Bridging the Gap Between Deep Learning and Hypothesis-Driven Analysis via Permutation Testing von Paschali, Magdalini, Zhao, Qingyu, Adeli, Ehsan, Pohl, Kilian M.

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Surgical Workflow Recognition: From Analysis of Challenges to Architectural Study von Czempiel, Tobias, Sharghi, Aidean, Paschali, Magdalini, Navab, Nassir, Mohareri, Omid

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3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation von Paschali, Magdalini, Gasperini, Stefano, Roy, Abhijit Guha, Fang, Michael Y.-S., Navab, Nassir

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Rethinking Ultrasound Augmentation: A Physics-Inspired Approach von Tirindelli, Maria, Eilers, Christine, Simson, Walter, Paschali, Magdalini, Azampour, Mohammad Farid, Navab, Nassir

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Self-supervised Learning for Physiologically-Based Pharmacokinetic Modeling in Dynamic PET von De Benetti, Francesca, Simson, Walter, Paschali, Magdalini, Sari, Hasan, Rominger, Axel, Shi, Kuangyu, Navab, Nassir, Wendler, Thomas

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Deep Multiple Instance Hashing for Scalable Medical Image Retrieval von Conjeti, Sailesh, Paschali, Magdalini, Katouzian, Amin, Navab, Nassir

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Manifold Exploring Data Augmentation with Geometric Transformations for Increased Performance and Robustness von Paschali, Magdalini, Simson, Walter, Roy, Abhijit Guha, Göbl, Rüdiger, Wachinger, Christian, Navab, Nassir

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Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs von Kim, Seong Tae, Goli, Leili, Paschali, Magdalini, Khakzar, Ashkan, Keicher, Matthias, Czempiel, Tobias, Burian, Egon, Braren, Rickmer, Navab, Nassir, Wendler, Thomas

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SOE: SO(3)-Equivariant 3D MRI Encoding von He, Shizhe, Paschali, Magdalini, Ouyang, Jiahong, Masood, Adnan, Chaudhari, Akshay, Adeli, Ehsan

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Spectral Graph Sample Weighting for Interpretable Sub-cohort Analysis in Predictive Models for Neuroimaging von Paschali, Magdalini, Jiang, Yu Hang, Siegel, Spencer, Gonzalez, Camila, Pohl, Kilian M, Chaudhari, Akshay, Zhao, Qingyu

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