Stages-based ECG signal analysis from traditional signal processing to machine learning approaches: A survey

M Wasimuddin, K Elleithy, AS Abuzneid… - IEEE …, 2020 - ieeexplore.ieee.org
Electrocardiogram (ECG) gives essential information about different cardiac conditions of
the human heart. Its analysis has been the main objective among the research community to …

[HTML][HTML] Analysis of various techniques for ECG signal in healthcare, past, present, and future

T Anbalagan, MK Nath, D Vijayalakshmi… - Biomedical Engineering …, 2023 - Elsevier
Cardiovascular diseases are the primary reason for mortality worldwide. As per WHO survey
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …

Explainable detection of myocardial infarction using deep learning models with Grad-CAM technique on ECG signals

V Jahmunah, EYK Ng, RS Tan, SL Oh… - Computers in Biology …, 2022 - Elsevier
Myocardial infarction (MI) accounts for a high number of deaths globally. In acute MI,
accurate electrocardiography (ECG) is important for timely diagnosis and intervention in the …

Hybrid CNN-LSTM deep learning model and ensemble technique for automatic detection of myocardial infarction using big ECG data

HM Rai, K Chatterjee - Applied Intelligence, 2022 - Springer
Automatic and accurate prognosis of myocardial infarction (MI) using electrocardiogram
(ECG) signals is a challenging task for the diagnosis and treatment of heart diseases. MI is …

Myocardial infarction detection based on deep neural network on imbalanced data

M Hammad, MH Alkinani, BB Gupta, AA Abd El-Latif - Multimedia Systems, 2022 - Springer
Myocardial infarction (MI) is an acute interruption of blood flow to the heart, which causes the
heart to suffer from a deficiency of blood and ischemia, so the heart muscle is damaged, and …

A comprehensive survey on ECG signals as new biometric modality for human authentication: Recent advances and future challenges

AN Uwaechia, DA Ramli - IEEE Access, 2021 - ieeexplore.ieee.org
Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field
and has recently received significant interest as a promising biometric trait. However, ECG …

[HTML][HTML] Deep learning for detecting and locating myocardial infarction by electrocardiogram: A literature review

P Xiong, SMY Lee, G Chan - Frontiers in cardiovascular medicine, 2022 - frontiersin.org
Myocardial infarction is a common cardiovascular disorder caused by prolonged ischemia,
and early diagnosis of myocardial infarction (MI) is critical for lifesaving. ECG is a simple and …

Deep learning methods for enhancing cone‐beam CT image quality toward adaptive radiation therapy: A systematic review

B Rusanov, GM Hassan, M Reynolds, M Sabet… - Medical …, 2022 - Wiley Online Library
The use of deep learning (DL) to improve cone‐beam CT (CBCT) image quality has gained
popularity as computational resources and algorithmic sophistication have advanced in …

An overview on state-of-the-art electrocardiogram signal processing methods: Traditional to AI-based approaches

VA Ardeti, VR Kolluru, GT Varghese… - Expert Systems with …, 2023 - Elsevier
Over the last decade, cardiovascular diseases (CVD's) are the leading cause of death
globally. Early prediction of CVD's can help in reducing the complications of high-risk …

Automated localization and severity period prediction of myocardial infarction with clinical interpretability based on deep learning and knowledge graph

C Han, S Pan, W Que, Z Wang, Y Zhai, L Shi - Expert Systems with …, 2022 - Elsevier
This paper presented an interpretable method for myocardial infarction (MI) localization and
severity period prediction using 12-leads electrocardiograms (ECG) based on deep learning …