Machine learning-based heart disease diagnosis: A systematic literature review

MM Ahsan, Z Siddique - Artificial Intelligence in Medicine, 2022 - Elsevier
Heart disease is one of the significant challenges in today's world and one of the leading
causes of many deaths worldwide. Recent advancement of machine learning (ML) …

Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions

HF Nweke, YW Teh, G Mujtaba, MA Al-Garadi - Information Fusion, 2019 - Elsevier
Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …

Practical intelligent diagnostic algorithm for wearable 12-lead ECG via self-supervised learning on large-scale dataset

J Lai, H Tan, J Wang, L Ji, J Guo, B Han, Y Shi… - Nature …, 2023 - nature.com
Cardiovascular disease is a major global public health problem, and intelligent diagnostic
approaches play an increasingly important role in the analysis of electrocardiograms …

ECG-based machine-learning algorithms for heartbeat classification

S Aziz, S Ahmed, MS Alouini - Scientific reports, 2021 - nature.com
Electrocardiogram (ECG) signals represent the electrical activity of the human hearts and
consist of several waveforms (P, QRS, and T). The duration and shape of each waveform …

Automated atrial fibrillation detection using a hybrid CNN-LSTM network on imbalanced ECG datasets

G Petmezas, K Haris, L Stefanopoulos… - … Signal Processing and …, 2021 - Elsevier
Atrial fibrillation is a heart arrhythmia strongly associated with other heart-related
complications that can increase the risk of strokes and heart failure. Manual …

Arrhythmia classification algorithm based on multi-head self-attention mechanism

Y Wang, G Yang, S Li, Y Li, L He, D Liu - Biomedical Signal Processing and …, 2023 - Elsevier
Cardiovascular disease is a major illness that causes human death, especially in the elderly.
Timely and accurate diagnosis of arrhythmia types is the key to early prevention and …

A new machine learning technique for an accurate diagnosis of coronary artery disease

M Abdar, W Książek, UR Acharya, RS Tan… - Computer methods and …, 2019 - Elsevier
Background and objective Coronary artery disease (CAD) is one of the commonest diseases
around the world. An early and accurate diagnosis of CAD allows a timely administration of …

An ensemble of deep learning-based multi-model for ECG heartbeats arrhythmia classification

E Essa, X **e - ieee access, 2021 - ieeexplore.ieee.org
An automatic system for heart arrhythmia classification can perform a substantial role in
managing and treating cardiovascular diseases. In this paper, a deep learning-based multi …

Digital twin perspective of fourth industrial and healthcare revolution

S Khan, T Arslan, T Ratnarajah - Ieee Access, 2022 - ieeexplore.ieee.org
Digital Twin (DT) is bringing revolution to our lives by a digital representation of the physical
system. DT is the creation of the joint usage of various technologies like Cyber-Physical …

RETRACTED ARTICLE: Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals

P Pławiak, UR Acharya - Neural Computing and Applications, 2020 - Springer
The heart disease is one of the most serious health problems in today's world. Over 50
million persons have cardiovascular diseases around the world. Our proposed work based …