A training strategy for hybrid models to break the curse of dimensionality von E. Samadi, Moein, Kiefer, Sandra, Fritsch, Sebastian Johaness, Bickenbach, Johannes, Schuppert, Andreas

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Noisecut: a python package for noise-tolerant classification of binary data using prior knowledge integration and max-cut solutions von Samadi, Moein E, Mirzaieazar, Hedieh, Mitsos, Alexander, Schuppert, Andreas

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Monitoring individualized glucose levels predicts risk for bradycardia in type 2 diabetes patients with chronic kidney disease: a pilot study von Farhadi Ghalati, Pejman, E. Samadi, Moein, Verket, Marlo, Balfanz, Paul, Müller-Wieland, Dirk, Jonas, Stephan, Napp, Andreas, Wanner, Christoph, Ketteler, Markus, Vassiliadou, Athina, Heidenreich, Stefan, Deserno, Thomas, Hetzel, Gudrun, Fliser, Danilo, Kelm, Malte, Floege, Jürgen, Marx, Nikolaus, Schuppert, Andreas

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A hybrid modeling framework for generalizable and interpretable predictions of ICU mortality across multiple hospitals von Samadi, Moein E., Guzman-Maldonado, Jorge, Nikulina, Kateryna, Mirzaieazar, Hedieh, Sharafutdinov, Konstantin, Fritsch, Sebastian Johannes, Schuppert, Andreas

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Application of convex hull analysis for the evaluation of data heterogeneity between patient populations of different origin and implications of hospital bias in downstream machine... von Sharafutdinov, Konstantin, Bhat, Jayesh S., Fritsch, Sebastian Johannes, Nikulina, Kateryna, E. Samadi, Moein, Polzin, Richard, Mayer, Hannah, Marx, Gernot, Bickenbach, Johannes, Schuppert, Andreas

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A training strategy for hybrid models to break the curse of dimensionality von Moein E. Samadi, Sandra Kiefer, Sebastian Johaness Fritsch, Johannes Bickenbach, Andreas Schuppert

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Smooth Kolmogorov Arnold networks enabling structural knowledge representation von Samadi, Moein E, Müller, Younes, Schuppert, Andreas

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Smooth Kolmogorov Arnold networks enabling structural knowledge representation von Samadi, Moein E, Müller, Younes, Schuppert, Andreas

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