ArticleNature communications2023
Practical intelligent diagnostic algorithm for wearable 12-lead ECG via self-supervised learning on large-scale dataset.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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
35 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Self-Supervised Contrastive Learning for Medical Time Series: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- BioShield-12: A 3D-Printed Conformal Chest Shield for Wireless 12-Lead ECG Acquisition.Sensors (Basel, Switzerland) · 2026Article
- A meta-learning method with reduced data requirements for training and updating deep learning models on wearable devices.Communications medicine · 2026Article
- Extracellular Vesicles in Wearable Delivery Systems for Cosmeceutical Applications.Advanced healthcare materials · 2026Review
- Convergence of Soft Electronics and Artificial Intelligence: From Materials to Intelligent Systems.Nano-micro letters · 2026Review
- WAVE: Wall-Aligned Vector Embedding for Self-Supervised Learning of Electrocardiograms.Bioengineering (Basel, Switzerland) · 2026Article
- CODE-II: a large-scale dataset for artificial intelligence in ECG analysis.NPJ digital medicine · 2026Article
- On-demand formation of ultrathin liquid metal hydrogel tattoos for conformal and low-impedance bioelectronics.Science advances · 2026Article
- Foundation models for electrocardiogram interpretation: clinical implications.European heart journal · 2026Article
- Review
- End-to-End Platform for Electrocardiogram Analysis and Model Fine-Tuning: Development and Validation Study.Journal of medical Internet research · 2026Article
- Contactless 12-lead electrocardiogram via deep computational radar.npj biomedical innovations · 2026Article
- Cardiac health assessment across scenarios and devices using a multimodal foundation model pretrained on data from 1.7 million individuals.Nature machine intelligence · 2026Article
- Design and Systematic Evaluation of a Multi-Layered Mattress System for Accurate, Unobtrusive Capacitive ECG Monitoring.Bioengineering (Basel, Switzerland) · 2025Article
- AI-enhanced flexible ECG patch for accurate heart disease diagnosis, optimal wear positioning, and interactive medical consultation.National science review · 2025Article
- Precision Medicine for Electrocardiogram Interpretation: Clinical Relevance, Challenges, and Advances.Reviews in cardiovascular medicine · 2025Review
- Flexible dry electrodes for electrocardiographic monitoring: Working principles, design strategies, and recent advances.iScience · 2025Review
- Transforming label-efficient decoding of healthcare wearables with self-supervised learning and "embedded" medical domain expertise.Communications engineering · 2025Article
- Robust screening of atrial fibrillation with distribution classification.Scientific reports · 2025Article
- Diagnostic accuracy of wearable ECG and assessment of ventricular repolarization and its cardiovascular risks post cold stress.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular disease is a major global public health problem, and intelligent diagnostic approaches play an increasingly important role in the analysis of electrocardiograms (ECGs). Convenient wearable ECG devices enable the detection of transient arrhythmias and improve patient health by making it possible to seek intervention during continuous monitoring. We collected 658,486 wearable 12-lead ECGs, among which 164,538 were annotated, and the remaining 493,948 were without diagnostic. We present four data augmentation operations and a self-supervised learning classification framework that can recognize 60 ECG diagnostic terms. Our model achieves an average area under the receiver-operating characteristic curve (AUROC) and average F1 score on the offline test of 0.975 and 0.575. The average sensitivity, specificity and F1-score during the 2-month online test are 0.736, 0.954 and 0.468, respectively. This approach offers real-time intelligent diagnosis, and detects abnormal segments in long-term ECG monitoring in the clinical setting for further diagnosis by cardiologists.
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.