Predicting Heart Wellness: A Survey on Machine Learning Approach

International Journal of Innovative Research in Computer and Communication Engineering 11 (12):12098-12103 (2023)
  Copy   BIBTEX

Abstract

The surge in heart diseases among individuals at a young age is becoming increasingly apparent, marking a concerning trend. This escalation can be primarily attributed to the profound impact of lifestyle choices on cardiovascular health. Sedentary habits, poor dietary practices, and heightened stress levels prevalent in contemporary living contribute significantly to this rise. Recognizing the relevance of lifestyle in this health issue is crucial as it highlights the need for preventive measures. Early prediction of the possibility of heart disease emerges as a pivotal strategy in addressing this challenge. Detecting potential risks at an early stage allows for timely interventions, potentially decreasing mortality rates and enhancing the life span of patients. In this context, the focus of the study is directed towards exploring and developing effective methods for early prediction, emphasizing the importance of proactive healthcare strategies in mitigating the growing burden of heart diseases in younger populations.

Analytics

Added to PP
2025-03-25

Downloads
15 (#106,494)

6 months
15 (#104,873)

Historical graph of downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.
How can I increase my downloads?