Toward practical screening of mortality risk: Insights from interpretable machine learning in NHANES
A parsimonious set of five predictors-age, gender, physical activity, TNT, and NT-proBNP-enabled efficient mortality risk stratification in NHANES, supporting their potential role in practical community screening.
Authors
- Yiting Lin (ORCID: https://orcid.org/0000-0002-8580-6884)
- Kai-Jen Chuang
Institutions
- National Taiwan University (TW)
- National Taiwan University Hospital (TW)
- Taipei Medical University (TW)
Publication Details
- Journal
- International Journal of Cardiology Cardiovascular Risk and Prevention
- Published
- 2026-02-12
- DOI
- https://doi.org/10.1016/j.ijcrp.2026.200595
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00