Predicting cardiovascular disease in patients with mental illness using machine learning
A machine learning model can accurately predict CVD risk among patients with mental illness using routinely collected electronic health record data. A decision support system building on this approach may aid primary CVD prevention in this high-risk population.
Authors
- Søren Dinesen Østergaard (ORCID: https://orcid.org/0000-0002-8032-6208)
- Kevin Kris Warnakula Olesen (ORCID: https://orcid.org/0000-0002-0560-3615)
- Lasse Hansen (ORCID: https://orcid.org/0000-0003-1113-4779)
- Andreas Aalkjær Danielsen (ORCID: https://orcid.org/0000-0002-6585-3616)
- Martin Bernstorff (ORCID: https://orcid.org/0000-0002-0234-5390)
Institutions
- Aarhus University (DK)
- Aarhus University Hospital (DK)
Publication Details
- Journal
- European Psychiatry
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1192/j.eurpsy.2025.1
- Citations
- 3
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 7.44
Funders
- Hjerteforeningen
- Aarhus Universitet
- Aarhus Universitetshospital
- University of Cambridge
- Lundbeckfonden
- Novo Nordisk
- Novo Nordisk Fonden
- Region Midtjylland
- H. Lundbeck A/S