A Novel Hybrid Learning Model for Early Diagnosis of Hypertension using IoMT Technologies

Authors

  • Dr. Brajesh Kumar

Keywords:

Hypertension, Early Diagnosis, Hybrid Machine Learning, Internet of Medical Things (IoMT), Ensemble Learning, Feature Selection

Abstract

Hypertension is a pervasive cardiovascular condition with significant health risks, necessitatingearly and accurate diagnosis to improve patient outcomes. The proliferation of Internet of MedicalThings (IoMT) devices enables continuous health monitoring, fostering real-time data collectionideal for advanced diagnostic models.

References

W. Whelton et al., “2017 ACC/AHA Hypertension Guideline,” Hypertension, vol. 71, no. 6, pp. e13–e115, 2018.

A. Islam et al., “IoMT-Based Remote Cardiovascular Disease Diagnosis,” IEEE Access, 2020.

Downloads

Published

2024-02-15

How to Cite

Dr. Brajesh Kumar. (2024). A Novel Hybrid Learning Model for Early Diagnosis of Hypertension using IoMT Technologies . Journal of Computational Analysis and Applications (JoCAAA), 33(2), 1676–1685. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/3461

Issue

Vol. 33 No. 2 (2024): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.