arXiv Machine Learning August 4, 2026 By Farhan Adam Mukadam, Harshit Mishra, Nachiket Makwana, Pradyot Tiwari, Subramani Kandasamy, KVS Hari

Automated ECG Interval Measurement and Wave Delineation Using Fast Fourier Convolution ResNet

Read the original on arXiv Machine Learning →

arXiv:2608. 00058v1 Announce Type: cross Abstract: Accurate measurement of ECG intervals, including PR, QRS duration, and QT/QTc, is central to cardiac diagnosis, yet the published ECG delineation literature evaluates performance almost exclusively as fiducial-point timing errors on small curated databases, rather than as clinical interval accuracy on large unselected cohorts.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI

Jul 7

ImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment

arXiv:2607. 05009v1 Announce Type: cross Abstract: Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular assessment, yet many clinical ECG records, particularly those digitized from ECG images, remain incomplete because of short display formats, incomplete waveform digitization, lead loss, or signal corruption.

By Xiaocheng Fang, Haoyu Wang, Jieyi Cai, Qinghao Zhao, Jun Li, Shanwei Zhang, Guangkun Nie, Yujie Xiao, Shun Huang, Jiarui Jin, Hongmin Liu, Guodong Wang, Shuohua Chen, Liming Lin, Shouling Wu, Hongyan Li, Shenda Hong

llms

arXiv AI

Aug 5

FOUND-AF: Benchmarking ECG Foundation Models for Atrial Fibrillation Detection

arXiv:2608. 03597v1 Announce Type: new Abstract: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is associated with increased risks of stroke, heart failure, and mortality.

By Amirhossein Taleshinosrati, Yangyang Wang, Atitaya Phoemsuk, Vahid Abolghasemi, Naser Hossein Motlagh, Sadasivan Puthusserypady, Daniel Teichmann, Abdolrahman Peimankar

rag benchmarks

arXiv AI

Jul 17

Angular Gaussian Supervised Contrastive Learning for Long-Tailed Electrocardiogram Arrhythmia Diagnosis

arXiv:2607. 14613v1 Announce Type: cross Abstract: Long-tailed label distributions reduce the reliability of deep learning for electrocardiogram (ECG) arrhythmia diagnosis, particularly for clinically important but rare abnormalities.

By Jin Dai, Qiuzhen Zhang, Chenyun Dai, Danmei Lan, Can Han

rag benchmarks

arXiv Machine Learning

Jul 28

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction

arXiv:2607. 23412v1 Announce Type: new Abstract: Electrocardiograms (ECGs) are widely used for cardiovascular risk prediction, yet models often fail to transfer across hospitals because of protocol, population, and measurement differences.

By Jie Lin, Weijie Sun, Sunil V. Kalmady, Anita Khalafbeigi, Abram Hindle, Padma Kaul, Russell Greiner

benchmarks

arXiv Machine Learning

Jul 31

ECG-InterpBench: Benchmarking the Interpretability of ECG Foundation Models with Matched-Scale Sparse Autoencoders

arXiv:2607. 27404v1 Announce Type: new Abstract: Existing benchmarks for electrocardiogram foundation models primarily evaluate downstream predictive performance, providing limited insight into whether their internal representations can be faithfully decomposed, clinically interpreted, or reproduced across independent analyses.

By Yixuan Duan, Wei Qiu

efficiency benchmarks safety

arXiv Machine Learning

5d ago

The Impact of Temporal Context Length and Encoding Strategies on Self-Supervised ECG Representation Learning

arXiv:2608. 12695v1 Announce Type: new Abstract: Self-supervised electrocardiogram (ECG) models are often trained on a few seconds of ECG signal and, increasingly, on discretized token sequences.

By Ahmed Sameh, Ramzi Al-Sharawi, Yogatheesan Varatharajah

llms rag efficiency

Related stories

ImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment

FOUND-AF: Benchmarking ECG Foundation Models for Atrial Fibrillation Detection

Angular Gaussian Supervised Contrastive Learning for Long-Tailed Electrocardiogram Arrhythmia Diagnosis

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction

ECG-InterpBench: Benchmarking the Interpretability of ECG Foundation Models with Matched-Scale Sparse Autoencoders

The Impact of Temporal Context Length and Encoding Strategies on Self-Supervised ECG Representation Learning