A novel IMW-mrmr feature selection approach for early detection of hypertension with HRV analysis
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s41870-024-02015-5.pdf
Reference35 articles.
1. Deka D, Deka B (2021) Stratification of high-risk hypertensive patients using hybrid heart rate variability features and boosting algorithms. IEEE Access 9:62665–62675
2. Jain P, Gajbhiye P, Tripathy RK, Acharya UR (2020) A two-stage deep CNN architecture for the classification of low-risk and high-risk hypertension classes using multi-lead ECG signals. Inform Med Unlocked 21:100479. https://doi.org/10.1016/j.imu.2020.100479
3. Evaluation of Heart Rate Variability in Hypertensive Subjects (no date). Thefreelibrary.com. Available at: https://www.thefreelibrary.com/Evaluation+of+Heart+Rate+Variability+in+Hypertensive+Subjects.-a0765922919. Accessed 7 Oct 2023.
4. Belinchon JML, Guerrero MAL, Alcaraz R (2022) How reproducible are heart rate variability indices along the time to predict cardiovascular events in hypertensive patients. In: 2022 E-Health and Bioengineering Conference (EHB). IEEE.
5. Bolin LP et al (2022) A pilot study investigating the relationship between heart rate variability and blood pressure in young adults at risk for cardiovascular disease. Clin Hypertens. https://doi.org/10.1186/s40885-021-00185-z
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