This paper is in the following e-collection/theme issue:

Artificial Intelligence (1754) Machine Learning (1748) Clinical Information and Decision Making (1665) Decision Support for Health Professionals (1347)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42181, first published .
Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study

Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study

Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study

Authors of this article:

Simon Schallmoser1, 2 Author Orcid Image ;   Thomas Zueger3, 4 Author Orcid Image ;   Mathias Kraus5 Author Orcid Image ;   Maytal Saar-Tsechansky6 Author Orcid Image ;   Christoph Stettler3 Author Orcid Image ;   Stefan Feuerriegel1, 2 Author Orcid Image
Article Authors Cited by (15) Tweetations (8) Metrics

Simon Schallmoser   1, 2 , MSc ;   Thomas Zueger   3, 4 , MD ;   Mathias Kraus   5 , PhD ;   Maytal Saar-Tsechansky   6 , PhD ;   Christoph Stettler   3 , MD ;   Stefan Feuerriegel   1, 2 , PhD

1 Institute of AI in Management, LMU Munich, Munich, Germany

2 Munich Center for Machine Learning (MCML), Munich, Germany

3 Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital Bern, University of Bern, Bern, Switzerland

4 Department of Endocrinology and Metabolic Diseases, Kantonsspital Olten, Olten, Switzerland

5 Institute of Information Systems, FAU Erlangen-Nuremberg, Nuremberg, Germany

6 The McCombs School of Business, The University of Texas at Austin, Austin, TX, United States

Corresponding Author: