Understanding random resampling techniques for class imbalance correction and their consequences on calibration and discrimination of clinical risk prediction models
Journal of Biomedical Informatics, vol. 155, pp. 104666
Authors 6
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Marco Piccininni corresponding
Charité - Universitätsmedizin Berlin · Hasso Plattner Institute · University of Potsdam
Affiliation as printed
Digital Health - Machine Learning Research Group, Hasso Plattner Institute for Digital Engineering, Potsdam, Germany; Digital Engineering Faculty, University of Potsdam, Potsdam, Germany; Institute of Public Health, Charité - Universitätsmedizin Berlin, Berlin, Germany. Electronic address: marco.piccininni@hpi.de
Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
Digital Health—Machine Learning Research Group, Hasso Plattner Institute for Digital Engineering, Potsdam, Germany
Institute of Public Health, Charité – Universitätsmedizin Berlin, Berlin, Germany
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Affiliation as printed
Department of Mathematics and Statistics, York University, Toronto, Canada
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KU Leuven · Leiden University Medical Center
Affiliation as printed
Department of Development and Regeneration, KU Leuven, Leuven, Belgium; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Leuven Unit for Health Technology Assessment Research (LUHTAR), KU Leuven, Leuven, Belgium
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
Department of Development and Regeneration, KU Leuven, Leuven, Belgium
Leuven Unit for Health Technology Assessment Research (LUHTAR), KU Leuven, Leuven, Belgium
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Charité - Universitätsmedizin Berlin · Center for Stroke Research Berlin
Affiliation as printed
Institute of Public Health, Charité - Universitätsmedizin Berlin, Berlin, Germany; Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, Berlin, Germany
Institute of Public Health, Charité – Universitätsmedizin Berlin, Berlin, Germany
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Icahn School of Medicine at Mount Sinai · Hasso Plattner Institute · University of Potsdam
Affiliation as printed
Digital Health - Machine Learning Research Group, Hasso Plattner Institute for Digital Engineering, Potsdam, Germany; Digital Engineering Faculty, University of Potsdam, Potsdam, Germany; Icahn School of Medicine at Mount Sinai, Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA
Digital Engineering Faculty, University of Potsdam, Potsdam, Germany
Digital Health—Machine Learning Research Group, Hasso Plattner Institute for Digital Engineering, Potsdam, Germany
Icahn School of Medicine at Mount Sinai, Hasso Plattner Institute for Digital Health at Mount Sinai, New York, NY, USA
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University Medical Center Utrecht · Utrecht University
Affiliation as printed
Julius Center for Health Sciences and Primary Care, UMC Utrecht, Utrecht University, Utrecht, the Netherlands
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References 29
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