Large-Scale Evaluation and Liver Disease Risk Prediction in Finland’s National Electronic Health Record System: Feasibility Study Using Real-World Data
We conclude that the current structured Kanta data is not enough for precise risk calculation for CLivD or other diseases where obesity, smoking, and alcohol use are important risk factors. Our simulations show up to 14% improvement in risk detection when adding support for missing input variables. Kanta shows the potential for implementing nationwide automated risk detection models that could result in improved disease prevention and public health.
Authors
- Fredrik O. Åberg (ORCID: https://orcid.org/0000-0002-3833-0705)
- Viljami Männikkö
- Olli-Pekka Hätinen
- Emmi Tikkanen (ORCID: https://orcid.org/0000-0003-1634-4134)
- Janne Tommola
Institutions
- University of Helsinki (FI)
- Tampere University of Applied Sciences (FI)
- Helsinki University Hospital (FI)
- Tampere University (FI)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-02-13
- DOI
- https://doi.org/10.2196/62978
- Citations
- 1
- Primary Topic
- Colorectal Cancer Screening and Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.05