Deep learning for ECG Arrhythmia detection and classification: an overview of progress for period 2017–2023

Y Ansari, O Mourad, K Qaraqe, E Serpedin - Frontiers in Physiology, 2023 - frontiersin.org
Cardiovascular diseases are a leading cause of mortality globally. Electrocardiography
(ECG) still represents the benchmark approach for identifying cardiac irregularities …

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 …

An efficient multilevel thresholding scheme for heart image segmentation using a hybrid generalized adversarial network

AM Reddy, KS Reddy, M Jayaram… - Journal of …, 2022 - Wiley Online Library
Most people worldwide, irrespective of their age, are suffering from massive cardiac arrest.
To detect heart attacks early, many researchers worked on the clinical datasets collected …

Golden standard or obsolete method? Review of ECG applications in clinical and experimental context

T Stracina, M Ronzhina, R Redina… - Frontiers in …, 2022 - frontiersin.org
Cardiovascular system and its functions under both physiological and pathophysiological
conditions have been studied for centuries. One of the most important steps in the …

Algorithms for automated diagnosis of cardiovascular diseases based on ECG data: A comprehensive systematic review

HV Denysyuk, RJ Pinto, PM Silva, RP Duarte… - Heliyon, 2023 - cell.com
The prevalence of cardiovascular diseases is increasing around the world. However, the
technology is evolving and can be monitored with low-cost sensors anywhere at any time …

Artificial intelligence for non-invasive glycaemic-events detection via ECG in a paediatric population: study protocol

M Andellini, S Haleem, M Angelini, M Ritrovato… - Health and …, 2023 - Springer
Abstract Purpose Paediatric Type 1 Diabetes (T1D) patients are at greater risk for
developing severe hypo and hyperglycaemic events due to poor glycaemic control. To …

DCFF-MTAD: a multivariate time-series anomaly detection model based on dual-channel feature fusion

Z Xu, Y Yang, X Gao, M Hu - Sensors, 2023 - mdpi.com
The detection of anomalies in multivariate time-series data is becoming increasingly
important in the automated and continuous monitoring of complex systems and devices due …

A Review on the Applications of Time‐Frequency Methods in ECG Analysis

BK Pradhan, BC Neelappu… - Journal of …, 2023 - Wiley Online Library
The joint time‐frequency analysis method represents a signal in both time and frequency.
Thus, it provides more information compared to other one‐dimensional methods. Several …

An efficient honey badger based Faster region CNN for chronc heart Failure prediction

SI Sherly, G Mathivanan - Biomedical Signal Processing and Control, 2023 - Elsevier
If the blood circulation of the heart is not adequate then it causes arrhythmias and
Congestive Heart Failure (CHF) which requires immediate medical attention or else it leads …

Exploring artificial intelligence algorithms for electrocardiogram (ECG) signal analysis: A comprehensive review

MF Safdar, RM Nowak, P Pałka - Computers in Biology and Medicine, 2023 - Elsevier
Electrocardiogram (ECG) are the physiological signals and a standard test to measure the
heart's electrical activity that depicts the movement of cardiac muscles. A review study has …