Intelligent Heart Disease Detector System Using Predictive Analytics

Sreejaa R T; Vidya Bharathi S; Sundarabalan D T; Vishal Dharsan S R; Vikas S

doi:10.64388/IREV9I5-1712327

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Intelligent Heart Disease Detector System Using Predictive Analytics

Sreejaa R T Vidya Bharathi S Sundarabalan D T Vishal Dharsan S R Vikas S

Subject area: Science,Engineering and Technology · Area of research: Web Based Application

DOI: 10.64388/IREV9I5-1712327

Abstract

With the increasing prevalence of cardiovascular diseases, efficient patient management has become a critical aspect of modern healthcare. This paper presents HeartCare, a web-based patient management system designed for cardiologists to monitor, evaluate, and communicate with patients efficiently. The system employs a role-based login mechanism for doctors and patients, provides a dynamic patient dashboard with search and filtering capabilities, and integrates an ECG analysis tool for real-time diagnostics. Built using HTML, Tailwind CSS, and Alpine.js, HeartCare offers a responsive and visually intuitive interface, supporting effective clinical decision-making. The system also incorporates a prototype messaging module, enabling secure communication between doctors and patients. This paper outlines the system architecture, implementation methodology, feature set, and potential benefits for healthcare professionals.

Keywords

Role-Based Access, Patient Dashboard, Cardiovascular Diseases, ECG Analysis, Web Application, Frontend Interactivity

References

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[2] Chen, Y., Zhang, X., & Li, J. (2020). Real-time ECG monitoring using web-based platforms. International Journal of Telemedicine and Applications, 2020, 1–10.

[3] Kumar, S., & Singh, A. (2019). Role-based access control for healthcare web applications. Proceedings of the 2019 IEEE International Conference on Healthcare Informatics, 67–74.

[4] Patel, V., & Gupta, R. (2018). Integration of web technologies for patient management systems. Journal of Biomedical Informatics, 83, 112–122.

[5] Ramesh, S., & Lee, H. (2021). Alpine.js and Tailwind CSS for responsive web-based healthcare dashboards. International Journal of Computer Applications, 182(25), 15–22.

[6] World Health Organization. (2020). Digital health interventions for cardiovascular disease management: Guidelines and best practices. Geneva: WHO.

[7] Zhang, L., & Li, P. (2019). Patient-centered web applications for chronic disease monitoring. Journal of Healthcare Engineering, 2019, 1–12.

[8] Duckett, J. (2014). HTML and CSS: Design and Build Websites. John Wiley & Sons.

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How to cite this paper

Sreejaa R T, Vidya Bharathi S, Sundarabalan D T, Vishal Dharsan S R, Vikas S "Intelligent Heart Disease Detector System Using Predictive Analytics" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 1691-1697 https://doi.org/10.64388/IREV9I5-1712327

Sreejaa R T, Vidya Bharathi S, Sundarabalan D T, Vishal Dharsan S R, Vikas S "Intelligent Heart Disease Detector System Using Predictive Analytics" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025, doi: https://doi.org/10.64388/IREV9I5-1712327

Sreejaa R T, Vidya Bharathi S, Sundarabalan D T, Vishal Dharsan S R, Vikas S (2025). Intelligent Heart Disease Detector System Using Predictive Analytics. Iconic Research And Engineering Journals, 9(5). doi: https://doi.org/10.64388/IREV9I5-1712327

Sreejaa R T, Vidya Bharathi S, Sundarabalan D T, Vishal Dharsan S R, Vikas S "Intelligent Heart Disease Detector System Using Predictive Analytics" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1712327

@article{1712327,
      author = {Sreejaa R T, Vidya Bharathi S, Sundarabalan D T, Vishal Dharsan S R, Vikas S},
      title = {Intelligent Heart Disease Detector System Using Predictive Analytics},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {5},
      pages = {1691-1697},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712327.pdf},
      abstract = {With the increasing prevalence of cardiovascular diseases, efficient patient management has become a critical aspect of modern healthcare. This paper presents HeartCare, a web-based patient management system designed for cardiologists to monitor, evaluate, and communicate with patients efficiently. The system employs a role-based login mechanism for doctors and patients, provides a dynamic patient dashboard with search and filtering capabilities, and integrates an ECG analysis tool for real-time diagnostics. Built using HTML, Tailwind CSS, and Alpine.js, HeartCare offers a responsive and visually intuitive interface, supporting effective clinical decision-making. The system also incorporates a prototype messaging module, enabling secure communication between doctors and patients. This paper outlines the system architecture, implementation methodology, feature set, and potential benefits for healthcare professionals.},
      keywords = {Role-Based Access, Patient Dashboard, Cardiovascular Diseases, ECG Analysis, Web Application, Frontend Interactivity},
      month = {November},
      doi = {https://doi.org/10.64388/IREV9I5-1712327}
  }