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Advanced Data Analytics in eHealth (334) Clinical Informatics (2132) Natural Language Processing (1225) Machine Learning (3043) Artificial Intelligence in Diabetes Care and Prevention (103)

Published on in Vol 14 (2026)

This is a member publication of Leiden University Medical Center

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80377, first published .
Doctor in white coat using a tablet with medical data, stethoscope visible.

Quantifying the Predictive Power of Social Determinants of Health in Cardiovascular Disease and Type 2 Diabetes Progression Using XGBoost: Retrospective Cohort Study

Quantifying the Predictive Power of Social Determinants of Health in Cardiovascular Disease and Type 2 Diabetes Progression Using XGBoost: Retrospective Cohort Study

Authors of this article:

Hielke Muizelaar1 Author Orcid Image ;   Marcel Haas1 Author Orcid Image ;   Maarten van Aken1, 2 Author Orcid Image ;   Rimke Vos1 Author Orcid Image ;   Marco Spruit1, 3 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Hielke Muizelaar   1 , MSci ;   Marcel Haas   1 , PhD ;   Maarten van Aken   1, 2 , MD, PhD ;   Rimke Vos   1 , PhD ;   Marco Spruit   1, 3 , Prof Dr

1 Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands

2 Department of Internal Medicine, Haga Hospital, The Hague, The Netherlands

3 Leiden Institute of Advanced Computer Science, Faculty of Science, Leiden University, Leiden, The Netherlands

Corresponding Author:

  • Hielke Muizelaar, MSci
  • Department of Public Health and Primary Care
  • Leiden University Medical Center
  • Albinusdreef 2
  • Leiden 2333ZA
  • The Netherlands
  • Phone: 31 715268444
  • Fax: 31 715142588
  • Email: h.j.muizelaar@lumc.nl