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Addressing Cardiovascular Health Disparities: From Modifiable Risks to Primary Care Interventions
Subject area: Science,Engineering and Technology · Area of research: Data Science
DOI: https://doi.org/10.64388/IREV9I6-1712914
Abstract
heart disease, also known as CVD, is the biggest reason people lose their lives in India. These complications may show clear signs or remain silent without any visible signs. Stopping them, identifying them early, and treating them on time are required to avoid poor quality of life and reduce the risk of death. A lot of research has shown that AI models can accurately predict stroke and coronary artery disease. These improvements for AI and machine learning are meant to do more than just help with early detection; they are also meant to make health interventions more personal. Researchers are still working on improving these technologies. There are also no studies that look at the causal links between the lifestyle factors that were used to make predictions. So, the goal of this study was to look at a lot of different causal links to see how certain lifestyle habits affect the risk of CVD. We used data from metabolic syndrome screening in the general population to build a prediction model for CVD in this study.
Keywords
Cardiovascular Disease, AI Models, Machine Learning, Prediction, Metabolic Syndrome
How to cite this paper
@article{1712914,
author = {Saranya Raj , Nikhil tiwary, Aman kumar },
title = {Addressing Cardiovascular Health Disparities: From Modifiable Risks to Primary Care Interventions},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {6},
pages = {1217-1220},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712914.pdf},
abstract = {heart disease, also known as CVD, is the biggest reason people lose their lives in India. These complications may show clear signs or remain silent without any visible signs. Stopping them, identifying them early, and treating them on time are required to avoid poor quality of life and reduce the risk of death. A lot of research has shown that AI models can accurately predict stroke and coronary artery disease. These improvements for AI and machine learning are meant to do more than just help with early detection; they are also meant to make health interventions more personal. Researchers are still working on improving these technologies. There are also no studies that look at the causal links between the lifestyle factors that were used to make predictions. So, the goal of this study was to look at a lot of different causal links to see how certain lifestyle habits affect the risk of CVD. We used data from metabolic syndrome screening in the general population to build a prediction model for CVD in this study.},
keywords = {Cardiovascular Disease, AI Models, Machine Learning, Prediction, Metabolic Syndrome},
month = {December},
doi = {https://doi.org/10.64388/IREV9I6-1712914}
}