Machine learning-based smart wearable system for cardiac arrest monitoring using hybrid computing-Reference-Cited by-同舟云学术

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Machine learning-based smart wearable system for cardiac arrest monitoring using hybrid computing

Published:2024-01 Issue: Volume:87 Page:105519
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Hannan Abdul,Cheema Sehrish Munawar,Pires Ivan Miguel^ORCID

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference54 articles.

1. Cardiovascular disease as a leading cause of death: how are pharmacists getting involved?;McNamara;Integr. Pharm. Res. Pract.,2021

2. Global cardiovascular diseases death rate prediction;Gaidai;Curr. Problems Cardiol.,2023

3. Cardiovascular disease (CVD): assessment, prediction and policy implications;Rehman;BMC Public Health,2021

4. Assessment of magnitude and spectrum of cardiovascular disease admissions and outcomes in saint paul hospital millennium medical college, addis ababa: A retrospective study;Mengistu;PLoS One,2022

5. Cardiovascular diseases (CVDs);WHO,2023

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1. Advanced Cardiovascular Health Management Through Comprehensive Risk Assessment and Predictive Modeling of Cardiac Arrest;2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO);2024-03-14

2. An optimized AdaBoost algorithm with atherosclerosis diagnostic applications: adaptive weight-adjustable boosting;The Journal of Supercomputing;2024-03-02

3. Exploring the Relationship Between Muscle-Enhancing Steroids and Heart Attacks: A Comprehensive Overview;International Journal of Pharmaceutical Research and Allied Sciences;2024

4. An Effective Hybrid Recommender System for Cardiovascular Illness Based on IoT;2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON);2023-12-01

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