Comparison of machine learning methods and standard logistic regression to improve inpatient quality measurement in two clinical use cases
Year: 2025
Type: article
Study design: Observational Study
Authors: Melissa Spoden, Thomas Datzmann, Patrik Dröge, Elisa Henke, Caroline Lang, Jessica Barlinn, Christoph Gumbinger, Tobias Helfen, Jan Christoph Katthagen, Christos Krogias, Jörg Nowotny, Pompiliu Piso, Christoph Reißfelder, Klaus-Dieter Schaser, Olaf Schoffer, Ekkehard Schuler, Nils Sommer, Simone Wesselmann, Uwe Zeymer, Jochen Schmitt, Christian Günster
Institutions: Wissenschaftliches Institut der AOK, University Hospital Carl Gustav Carus, Zentrum für Evidenzbasierte Gesundheitsversorgung, Technische Universität Dresden, Heidelberg University, University Hospital Heidelberg, LMU Klinikum, Ludwig-Maximilians-Universität München, University of Münster, University Hospital Münster, University Hospitals of the Ruhr-University of Bochum, Ruhr University Bochum, Krankenhaus Barmherzige Brüder, Medizinische Fakultät Mannheim, Helios Kliniken, University of Bonn, University Hospital Bonn, Klinikum Ludwigshafen
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: closed
OpenAlex ID: W4411125605