Addressing Cardiovascular Health Disparities: From Modifiable Risks to Primary Care Interventions

References

[1] ElSofany, H., Bouallegue, B., & Abd ElLatif, Y.M. (2024). A proposed technique for predicting heart disease using feature selection and multimodel ensemble. Scientific Reports, 14, 23277.

[2] Ahmad, A.A., & Polat, H. (2023). Prediction of heart disease using ML with jellyfish optimization. Diagnostics (Basel).

[3] Bhatt, C.M., Patel, P., Ghetia, T., & Mazzeo, P.L. (2023). Effective heart disease prediction using machine learning techniques. Algorithms, 16(2), 88.

[4] Subramani, S., et al. (2023). Cardiovascular diseases prediction by ML: A comprehensive review. Frontiers in Medicine.

[5] Hajiarbabi, M. (2024). Heart disease detection using machine learning: A narrative review. JMAI.

[6] Hossain, S., et al. (2024). ML approach for predicting cardiovascular disease. BMC Cardiovascular Disorders.

[7] Banerjee, T. (2025). Systematic review of ML in heart disease prediction. PMC.

[8] Azimi Lamir, A., et al. (2025). Comprehensive ML framework for heart disease prediction. arXiv:2505.09969.

[9] Yi, J., Yu, P., Huang, T., et al. (2024). Transformer model for heart disease prediction using PSO. arXiv:2412.02801.

[10] Karmakar, R., Ghosh, U., Pal, A., et al. (2024). Data balancing expert system for heart disease prediction. arXiv:2407.18606.

[11] Muhammad, Y., Tahir, M., Hayat, M., & Chong, K.T. (2020). Early detection of heart disease using intelligent computational models. Scientific Reports.

[12] Ahsan, M.M., Luna, S.A., & Siddique, Z. (2022). MLbased disease diagnosis: A review. Healthcare (Basel).

[13] Logabiraman, G., et al. (2024). Heart disease prediction using ML algorithms. MATEC Web of Conferences.

[14] Ramalingam, V.V., Dandapath, A., & Karthik Raja, M. (2018). Heart disease prediction using ML techniques. IJET.

[15] Nagavelli, U., Samanta, D., & Chakraborty, P. (2022). Heart disease detection models using ML. Journal of Healthcare Engineering.

[16] Maiga, J., & Hungilo, G.G. (2019). Comparison of ML models for cardiovascular prediction. ICIMCIS Proceedings.

[17] Ingole, B.S., et al. (2024). Advancements in heart disease prediction using ML. arXiv:2410.14738.

[18] Ye, Z., An, S., Gao, Y., et al. (2023). Prediction of mortality in CKD patients with CAD using ML. European Journal of Medical Research.

[19] Dinov, I.D. (2023). Data Science and Predictive Analytics: Biomedical Applications. Springer.

[20] Singh, A., et al. (2024). Heart disease detection using machine learning models. Procedia Computer Science.

@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}
  }