Machine learning-based identification of determinants of pulse pressure in pregnant women
Machine learning methods applied to longitudinal antenatal data provide a flexible and effective framework for modeling pulse pressure dynamics during pregnancy. This approach enhances understanding of key clinical and temporal determinants and may support improved cardiovascular risk assessment in maternal health care settings.
Authors
- Merga Abdissa Aga (ORCID: https://orcid.org/0000-0003-4291-6247)
Institutions
- Ethiopian Civil Service University (ET)
Publication Details
- Journal
- Global Epidemiology
- Published
- 2026-01-07
- DOI
- https://doi.org/10.1016/j.gloepi.2026.100245
- Primary Topic
- Heart Rate Variability and Autonomic Control
- Type
- article
- Field-Weighted Citation Impact
- 0.00