Supervised machine learning techniques for the classification of metabolic disorders in newborns. - Christian Baumgartner; Christian Böhm 001; Daniela Baumgartner; G. Marini; Klaus Weinberger; B. Olgemöller; B. Liebl; A. A. Roscher (Bioinform., 2004)

Modelling of classification rules on metabolic patterns including machine learning and expert knowledge. - Christian Baumgartner; Christian Böhm 001; Daniela Baumgartner (J. Biomed. Informatics, 2005)

A bioinformatics framework for genotype-phenotype correlation in humans with Marfan syndrome caused by FBN1 gene mutations. - Christian Baumgartner; Gábor Mátyás; Beat Steinmann; Martin Eberle; Jörg I. Stein; Daniela Baumgartner (J. Biomed. Informatics, 2006)

Bioinformatic-driven search for metabolic biomarkers in disease. - Christian Baumgartner; Melanie Osl; Michael Netzer; Daniela Baumgartner (J. Clin. Bioinform., 2011)

Deep learning in spatiotemporal cardiac imaging: A review of methodologies and clinical usability. - Karen Andrea Lara Hernandez; Theresa Rienmüller; Daniela Baumgartner; Christian Baumgartner (Comput. Biol. Medicine, 2021)

A Systematic Review of the Transthoracic Impedance during Cardiac Defibrillation. - Yasmine Heyer; Daniela Baumgartner; Christian Baumgartner (Sensors, 2022)

Deep Learning-Based Image Registration in Dynamic Myocardial Perfusion CT Imaging. - Karen Andrea Lara Hernandez; Theresa Rienmüller; Ivan Alexander Juárez; Michaelle Alexander Perez Riz; Favio Reyna; Daniela Baumgartner; Vladimir N. Makarenko; Olga L. Bockeria; Musaffar F. Maksudov; Rainer Rienmüller; Christian Baumgartner (IEEE Trans. Medical Imaging, 2023)