Machine learning techniques for improved prediction of cardiovascular diseases using integrated healthcare data.

ABSTRACT: Cardiovascular disease continues to cause an important global health challenge, highlighting the critical importance of early detection in mitigating cardiac-related issues. There is a significant demand for reliable diagnostic alternatives. Taking advantage of health data through diverse machine learning algorithms may offer a more precise diagnostic approach. Machine learning-based decision support systems that utilize patients' clinical parameters present a promising solution for diagnosing cardiovascular disease. In this research, we collected extensive publicly available healthcare records. We integrated medical datasets based on common features to implement several machine learning models aimed at exploring the potential for more robust predictions of cardiovascular disease (CVD). Th

SUBMITTER: Kahraman A 

PROVIDER: S-EPMC12723862 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature