SynthesisBiomedical engineering online2025
Deep learning and electrocardiography: systematic review of current techniques in cardiovascular disease diagnosis and management.
Synthesis in Biomedical engineering online, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Continuous Glucose Monitoring Data Compression Using Peak-Nadir Encoding in Diabetes: Method Development and Evaluation.JMIR biomedical engineering · 2026Article
- Autonomous Agents for Auditable Cardiovascular Artificial Intelligence Development.medRxiv : the preprint server for health sciences · 2026Article
- Advances in the Interpretation of the Electrocardiogram by Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2026Review
- An Intelligent IoT-Compatible Arrhythmia Detection System Using a Hybrid Vision Transformer-LSTM Framework.Cardiovascular engineering and technology · 2026Article
- Integrating AI-Driven Diagnostics in Arrhythmia Care to Enhance Patient Outcomes: A Narrative Review.Cureus · 2026Review
- Artificial Intelligence for the Detection of Hypertrophic Cardiomyopathy From Standard Electrocardiogram.JACC. Advances · 2026Article
- Functional, molecular, and digital measurements of biological age.The Journal of clinical investigation · 2026Review
- Artificial intelligence-predicted ECG age gap as a biomarker: bias-adjusted correlation with mortality and cardiovascular risk factors.European heart journal. Digital health · 2026Article
- A joint CNN-Bi-LSTM-transformer architecture with SHAP explanations for multi-label arrhythmia detection from 12-lead ECGs.Scientific reports · 2026Article
- Scientific Publication Trend: Using Advanced Technologies in Cardiovascular Disease Research in theJournal of cardiovascular development and disease · 2026Article
- The Evolving Role of Artificial Intelligence and Machine Learning in the Wearable Electrocardiogram: A Primer on Wearable-Enabled Prediction of Cardiac Dysfunction.Bioengineering (Basel, Switzerland) · 2026Review
- Digitizing paper ECGs at scale: an open-source algorithm for clinical research.NPJ digital medicine · 2026Article
- Challenges in the Classification of Cardiac Arrhythmias and Ischemia Using End-to-End Deep Learning and the Electrocardiogram: A Systematic Review.Diagnostics (Basel, Switzerland) · 2026Review
- Deep Learning-Based Prediction Model for Cardiac Resynchronization Therapy Responders Using Electrocardiogram Data.Journal of cardiovascular electrophysiology · 2026Article
- Web-Based Graphical User Interface Design Integrating MATLAB Server for the Mathematical Model of Human Cardiovascular-Respiratory System.Bioinformatics and biology insights · 2026Article
- Improving ECG Interpretation Skills Among Healthcare Providers at Aswan University Hospitals: A Clinical Audit.Cureus · 2026Article
- ECG sonification methods for robust and generalizable clinical decision support.NPJ digital medicine · 2025Article
- Deep Learning R-Wave Detection for Electrocardiographic Gating in Cardiac MRI.Radiology. Cardiothoracic imaging · 2025Article
- Systematic Review of Artificial Intelligence and Electrocardiography for Cardiovascular Disease Diagnosis.Bioengineering (Basel, Switzerland) · 2025Review
- Artificial Intelligence in Cardiac Electrophysiology: A Clinically Oriented Review with Engineering Primers.Bioengineering (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper reviews the recent advancements in the application of deep learning combined with electrocardiography (ECG) within the domain of cardiovascular diseases, systematically examining 198 high-quality publications. Through meticulous categorization and hierarchical segmentation, it provides an exhaustive depiction of the current landscape across various cardiovascular ailments. Our study aspires to furnish interested readers with a comprehensive guide, thereby igniting enthusiasm for further, in-depth exploration and research in this realm.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.