Key factors in predictive analysis of cardiovascular risks in public health

Key factors in predictive analysis of cardiovascular risks in public health

Abstract This research emphasizes the role of analytics in evaluating the risk of disease (CVD) focusing on thorough data preparation and feature engineering for accurate predictions. We studied machine learning (ML) and learning (DL) models, such as Logistic Regression (LR) Random Forest (RF) Gradi...

Full description

Saved in:
Bibliographic Details
Main Authors: Ghazi I. Al Jowf, Manjur Kolhar
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Cardiovascular
Machine learning
Deep learning
Regression
Random forest
Gradient boosting machines
Online Access:https://doi.org/10.1038/s41598-025-07874-x
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-07874-x

Similar Items