[HTML][HTML] A systematic review of machine learning and IoT applied to the prediction and monitoring of cardiovascular diseases
A Cuevas-Chavez, Y Hernandez, J Ortiz-Hernandez… - Healthcare, 2023 - mdpi.com
According to the Pan American Health Organization, cardiovascular disease is the leading
cause of death worldwide, claiming an estimated 17.9 million lives each year. This paper …
cause of death worldwide, claiming an estimated 17.9 million lives each year. This paper …
Deep Learning Technologies for Time Series Abnormality Detection in Healthcare: A Review
X Yang, X Qi, X Zhou - IEEE Access, 2023 - ieeexplore.ieee.org
Medical time series data often exhibit intricate and dynamic patterns. With the rapid
advancement of medical digitization, deep learning-based time series anomaly detection …
advancement of medical digitization, deep learning-based time series anomaly detection …
[HTML][HTML] Federated learning with hyper-parameter optimization
Federated Learning is a new approach for distributed training of a deep learning model on
data scattered across a large number of clients while ensuring data privacy. However, this …
data scattered across a large number of clients while ensuring data privacy. However, this …
[HTML][HTML] Electrocardiogram Signals Classification Using Deep-Learning-Based Incorporated Convolutional Neural Network and Long Short-Term Memory Framework
A Eleyan, E Alboghbaish - Computers, 2024 - mdpi.com
Cardiovascular diseases (CVDs) like arrhythmia and heart failure remain the world's leading
cause of death. These conditions can be triggered by high blood pressure, diabetes, and …
cause of death. These conditions can be triggered by high blood pressure, diabetes, and …
Federated Learning and Differential Privacy Techniques on Multi-hospital Population-scale Electrocardiogram Data
V Agrawal, SV Kalmady, VM Malipeddi… - arXiv preprint arXiv …, 2024 - arxiv.org
This research paper explores ways to apply Federated Learning (FL) and Differential
Privacy (DP) techniques to population-scale Electrocardiogram (ECG) data. The study …
Privacy (DP) techniques to population-scale Electrocardiogram (ECG) data. The study …
An Adaptive Threshold-Based Semi-Supervised Learning Method for Cardiovascular Disease Detection
J Shi, Z Li, W Liu, H Zhang, D Luo, Y Ge, S Chang… - Information …, 2024 - Elsevier
Deep cardiovascular disease (CVD) detection usually achieves good performance with
large-scale labeled electrocardiograms (ECGs), but manual labeling of ECGs is tedious …
large-scale labeled electrocardiograms (ECGs), but manual labeling of ECGs is tedious …
AI-Driven Real-Time Classification of ECG Signals for Cardiac Monitoring Using i-AlexNet Architecture
The healthcare industry has evolved with the advent of artificial intelligence (AI), which uses
advanced computational methods and algorithms, leading to quicker inspection, forecasting …
advanced computational methods and algorithms, leading to quicker inspection, forecasting …
Privacy-Preserving ECG Data Analysis with Differential Privacy: A Literature Review and A Case Study
Differential privacy has become the preeminent technique to protect the privacy of
individuals in a database while allowing useful results from data analysis to be shared …
individuals in a database while allowing useful results from data analysis to be shared …