Research graph
References from Distributional reliability explanation for diffusion-based electrocardiogram abnormality risk prediction. Local targets link to admitted publications; unresolved targets remain external evidence.
State-of-the-art deep learning methods on electrocardiogram data: systematic review
10.2196/38454 · 2022 · External reference
DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms
10.1038/s41598-020-73126-9 · 2020 · External reference
Deep learning for electrocardiogram interpretation: bench to bedside
10.1111/eci.70002 · 2025 · External reference
Deep learning for ECG analysis: benchmarks and insights from PTB-XL
10.1109/jbhi.2020.3022989 · 2021 · External reference
Machine learning models for automated interpretation of 12-lead electrocardiographic signals: a narrative review of techniques, challenges, achievements and clinical relevance
10.21037/jmai-22-94 · 2023 · External reference
Enhanced ECG beat classification using a hybrid transformer-CNN model on the PTB-Xl dataset
2025 · External reference
Explainable AI decision model for ECG data of cardiac disorders
10.1016/j.bspc.2022.103584 · 2022 · External reference
Explainable AI for automatic heart disease diagnosis using 3DFMMecg features: a novel ECG-based approach
10.1016/j.bspc.2025.109085 · 2026 · External reference
Explainable deep learning-based approach for multilabel classification of electrocardiogram
10.1109/tem.2021.3104751 · 2023 · External reference
Explainable artificial intelligence for heart rate variability in ECG signal
10.1049/htl.2020.0033 · 2020 · External reference
A new approach of transparent and explainable artificial intelligence technique for patient-specific ECG beat classification
10.1109/lsens.2023.3268677 · 2023 · External reference
Signal or noise? Evaluating commonly used attribution methods for explaining deep neural networks in electrocardiogram classification
10.1093/ehjdh/ztag038 · 2026 · External reference
Improving ECG classification interpretability using saliency maps
2020 · External reference
A joint CNN-Bi-LSTM-transformer architecture with SHAP explanations for multi-label arrhythmia detection from 12-lead ECGs
10.1038/s41598-026-40925-5 · 2026 · External reference
Evaluating gradient-based explanation methods for neural network ECG analysis using heatmaps
10.1093/jamia/ocae280 · 2025 · External reference
Designing ECG monitoring healthcare system with federated transfer learning and explainable AI
10.1016/j.knosys.2021.107763 · 2022 · External reference
Explainable AI for specific arrhythmia detection: SHAP-based insights from multi-lead ECG data
10.1007/s40846-025-00949-0 · 2025 · External reference
A unified approach to interpreting model predictions
2017 · External reference
Uncertainty in machine learning feature importance for climate science: a comparative analysis of SHAP, PDP, and gain-based methods
10.1007/s00704-025-05703-9 · 2025 · External reference
DREA: a probabilistic distributional attribution framework for trustworthy explanations in diffusion-based predictive models
10.21203/rs.3.rs-9969649/v1 · 2026 · External reference
Confident learning: estimating uncertainty in dataset labels
10.1613/jair.1.12125 · 2021 · External reference
An overview of inference methods in probabilistic classifier chains for multilabel classification
10.1002/widm.1185 · 2016 · External reference
Stochastic model updating using conditional diffusion-based probabilistic generative models
10.1016/j.ymssp.2026.113891 · 2026 · External reference
Diffusion models in vision: a survey
10.1109/tpami.2023.3261988 · 2023 · External reference
Tackling prediction uncertainty in machine learning for healthcare
10.1038/s41551-022-00988-x · 2023 · External reference
Explainable deep learning-based techniques for ECG-based heart disease classification: a systematic literature review and future direction
10.1016/j.compbiomed.2025.111324 · 2025 · External reference
Exploring interpretable AI methods for ECG data classification
2024 · External reference
Synthetic ECG signal generation using probabilistic diffusion models
10.1109/access.2023.3296542 · 2023 · External reference
Diffusion-based conditional ECG generation with structured state space models
10.1016/j.compbiomed.2023.107115 · 2023 · External reference
Uncertainty-guided diffusion model for high-fidelity ECG synthesis and classification
10.1111/exsy.70070 · 2025 · External reference
PTB-XL, a large publicly available electrocardiography dataset
10.1038/s41597-020-0495-6 · 2020 · External reference
ECG heartbeat classification: a deep transferable representation
2018 · External reference
Random forests
10.1023/a:1010933404324 · 2001 · External reference
Probability machines: consistent probability estimation using nonparametric learning machines
10.3414/me00-01-0052 · 2012 · External reference
ECG signal classification using deep learning techniques based on the PTB-XL dataset
10.3390/e23091121 · 2021 · External reference
Interpretable deep learning models for arrhythmia classification based on ECG signals using PTB-X dataset
10.3390/diagnostics15151950 · 2025 · External reference
Automated posterior myocardial infarction detection from vectorcardiogram and derived vectorcardiogram signals using MVFBSE-EWT method
10.1016/j.dsp.2025.105244 · 2025 · External reference
Detection of coronary microvascular dysfunction based on machine learning algorithm with multidimensional temporal-spatial features from electrocardiogram
10.1088/1361-6579/ae7799 · 2026 · External reference
ECG arrhythmia classification via wavelet-driven feature extraction and swarm-optimised gradient boosting
10.1016/j.compbiomed.2026.111839 · 2026 · External reference
Precordial bipolar leads: a new method to study anterior acute myocardial infarction
10.1016/j.jelectrocard.2019.12.017 · 2020 · External reference
Heartbeat classification using morphological and dynamic features of ECG signals
10.1109/tbme.2012.2213253 · 2012 · External reference
Arrhythmia recognition and classification using combined parametric and visual pattern features of ECG morphology
10.1109/access.2020.2979256 · 2020 · External reference
aVR—the forgotten lead
2010 · External reference
Clinical utility of aVR—the neglected electrocardiographic lead
10.1111/j.1542-474x.2010.00359.x · 2010 · External reference
Using explainable AI to investigate electrocardiogram changes during healthy aging—from expert features to raw signals
10.1371/journal.pone.0302024 · 2024 · External reference
PTB-XL, a large publicly available electrocardiography dataset (version 1.0.3)
10.13026/kfzx-aw45 · 2022 · External reference
