A review of evaluation approaches for explainable AI with applications in cardiology

AM Salih, IB Galazzo, P Gkontra, E Rauseo… - Artificial Intelligence …, 2024 - Springer
Explainable artificial intelligence (XAI) elucidates the decision-making process of complex AI
models and is important in building trust in model predictions. XAI explanations themselves …

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 …

MSGformer: A multi-scale grid transformer network for 12-lead ECG arrhythmia detection

C Ji, L Wang, J Qin, L Liu, Y Han, Z Wang - Biomedical Signal Processing …, 2024 - Elsevier
The electrocardiogram (ECG) is a ubiquitous medical diagnostic tool employed to identify
arrhythmias that are characterized by anomalous waveform morphology and erratic …

Advancing cardiac diagnostics: Exceptional accuracy in abnormal ECG signal classification with cascading deep learning and explainability analysis

W Zeng, L Shan, C Yuan, S Du - Applied Soft Computing, 2024 - Elsevier
Arrhythmias, cardiac rhythm disorders, demand precise diagnosis for effective treatment
planning, emphasizing the crucial role of electrocardiogram (ECG) signal interpretation …

IM-ECG: An interpretable framework for arrhythmia detection using multi-lead ECG

R Tao, L Wang, Y **ong, YR Zeng - Expert Systems with Applications, 2024 - Elsevier
Multi-lead electrocardiogram (ECG) is a fundamental and reliable diagnostic tool for the
detection of heart arrhythmias. An increasing number of deep neural network models have …

Detecting COVID-19 from digitized ECG printouts using 1D convolutional neural networks

T Nguyen, HH Pham, KH Le, AT Nguyen, T Thanh… - PLoS …, 2022 - journals.plos.org
The COVID-19 pandemic has exposed the vulnerability of healthcare services worldwide,
raising the need to develop novel tools to provide rapid and cost-effective screening and …

Explainable artificial intelligence for medical applications: A review

Q Sun, A Akman, BW Schuller - ACM Transactions on Computing for …, 2024 - dl.acm.org
The continuous development of artificial intelligence (AI) theory has propelled this field to
unprecedented heights, owing to the relentless efforts of scholars and researchers. In the …

[HTML][HTML] DCETEN: A lightweight ECG automatic classification network based on Transformer model

F Jiang, J **ao, L Liu, C Wang - Digital Communications and Networks, 2024 - Elsevier
Abstract Currently, Cardiovascular Disease (CVD) remains a significant contributor to
premature mortality and escalating health care expenses. Early and accurate detection is …

Enhancing deep learning-based 3-lead ecg classification with heartbeat counting and demographic data integration

KH Le, HH Pham, TBT Nguyen… - 2022 IEEE-EMBS …, 2022 - ieeexplore.ieee.org
An increasing number of people are being diagnosed with cardiovascular diseases (CVDs),
the leading cause of death globally. The gold standard for identifying these heart problems …

[PDF][PDF] Cardioview: a framework for detection premature ventricular contractions with explainable artificial intelligence

G Arienzo, AA Citarella, F De Marco… - INI-DH 2024: Workshop …, 2024 - ceur-ws.org
Artificial Intelligence plays a vital role in disease diagnosis, but effectively classifying diverse
Premature Ventricular Contraction (PVC) subtypes remains a challenge. While computer …