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   Articles with "single lead" as a keyword



Artificial Intelligence-Enabled Prediction of Heart Failure Risk From Single-Lead Electrocardiograms.

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recommendations! Published in 2025 at "JAMA cardiology"

DOI: 10.1001/jamacardio.2025.0492

Abstract: Importance Despite the availability of disease-modifying therapies, scalable strategies for heart failure (HF) risk stratification remain elusive. Portable devices capable of recording single-lead electrocardiograms (ECGs) may enable large-scale community-based risk assessment. Objective To evaluate whether… read more here.

Keywords: ecg; risk; single lead; median iqr ... See more keywords
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Deep convolutional architecture-based hybrid learning for sleep arousal events detection through single-lead EEG signals.

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recommendations! Published in 2023 at "Brain and behavior"

DOI: 10.1002/brb3.3028

Abstract: INTRODUCTION Detecting arousal events during sleep is a challenging, time-consuming, and costly process that requires neurology knowledge. Even though similar automated systems detect sleep stages exclusively, early detection of sleep events can assist in identifying… read more here.

Keywords: arousal events; single lead; detection; sleep arousal ... See more keywords

Arrhythmia classification from single-lead ECG signals using the inter-patient paradigm

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recommendations! Published in 2021 at "Computer methods and programs in biomedicine"

DOI: 10.1016/j.cmpb.2021.105948

Abstract: BACKGROUND AND OBJECTIVES Arrhythmia is a heart disease characterized by the change in the regularity of the heartbeat. Since this disorder can occur sporadically, Holter devices are used for continuous long-term monitoring of the subject's… read more here.

Keywords: patient paradigm; system; ecg; inter patient ... See more keywords

Study on the use of standard 12-lead ECG data for rhythm-type ECG classification problems

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recommendations! Published in 2022 at "Computer methods and programs in biomedicine"

DOI: 10.1016/j.cmpb.2021.106521

Abstract: BACKGROUND AND OBJECTIVES Most deep-learning-related methodologies for electrocardiogram (ECG) classification are focused on finding an optimal deep-learning architecture to improve classification performance. However, in this study, we proposed a methodology for fusion of various single-lead… read more here.

Keywords: ecg; lead; single lead; lead ecg ... See more keywords
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Usefulness, pitfalls and interpretation of handheld single‑lead electrocardiograms.

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recommendations! Published in 2021 at "Journal of electrocardiology"

DOI: 10.1016/j.jelectrocard.2021.02.011

Abstract: Single‑lead electrocardiograms (1 L-ECGs) are increasingly used in (pre)clinical settings for the detection and monitoring of a range of rhythm and conduction disorders. In this short communication paper, we aim to provide an overview of the… read more here.

Keywords: lead; usefulness pitfalls; pitfalls interpretation; single lead ... See more keywords
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APPLICABILITY OF NOVEL, CLASS ACTIVATION MAPS (CAM) IN THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE-GUIDED, SINGLE AND 12-LEAD ECG TO DETECT ST-ELEVATION MYOCARDIAL INFARCTION

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recommendations! Published in 2020 at "Journal of the American College of Cardiology"

DOI: 10.1016/s0735-1097(20)34101-2

Abstract: Convolutional Neural Networks (CNN) are seamlessly integrated into many fields, including image recognition. CAM are able to recognize specific regions of images for their classification. We applied CAM and discovered discriminative segments for the detection… read more here.

Keywords: applicability novel; guided single; class activation; activation maps ... See more keywords

An integrated algorithm for single lead electrocardiogram signal analysis using deep learning with 12-lead data

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-18910-1

Abstract: Artificial intelligence (AI) algorithms have demonstrated remarkable efficiency in analyzing 12-lead clinical electrocardiogram (ECG) signals. This has sparked interest in leveraging cost-effective and user-friendly smart devices based on single-lead ECG (SL-ECG) for diagnosing heart dysfunction.… read more here.

Keywords: ecg; lead clinical; lead; analysis ... See more keywords

Predict alone, decide together: cardiac abnormality detection based on single lead classifier voting

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recommendations! Published in 2022 at "Physiological Measurement"

DOI: 10.1088/1361-6579/ac66b9

Abstract: Objective. A classifier based on weighted voting of multiple single-lead based models combining deep learning (DL) representation and hand-crafted features was developed to classify 26 cardiac abnormalities from different lead subsets of short-term electrocardiograms (ECG).… read more here.

Keywords: classifier; voting; single lead; lead subsets ... See more keywords

Sleep apnea detection from single-lead electrocardiogram signals using effective deep-shallow fusion network

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recommendations! Published in 2024 at "Physiological Measurement"

DOI: 10.1088/1361-6579/ad205a

Abstract: Objective. Explore a network architecture that can efficiently perform single-lead electrocardiogram (ECG) sleep apnea (SA) detection by utilizing the beneficial information of extended ECG segments and reducing the impact of their noisy information. Approach. We… read more here.

Keywords: detection; ecg dataset; network; single lead ... See more keywords

Enriching artificial intelligence ST-elevation myocardial infarction (STEMI) detection algorithms with differential diagnoses

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recommendations! Published in 2020 at "European Heart Journal"

DOI: 10.1093/ehjci/ehaa946.1776

Abstract: STEMI outcomes, although improved with systems of care, are hamstrung by delayed presentation and prevaricates of a 12-lead ECG. We report an artificial intelligence (AI) guided, single lead EKG algorithm for a self-administered tool to… read more here.

Keywords: stemi; differential diagnoses; artificial intelligence; lead ... See more keywords

Mobile single-lead ECG atrial fibrillation prediction enhancement integrated by standard ECG algorithm with Deep learning model

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recommendations! Published in 2024 at "European Heart Journal"

DOI: 10.1093/eurheartj/ehae666.3431

Abstract: Artificial intelligence (AI) using electrocardiogram (ECG) enabled to predict atrial fibrillation (AF) in patients without documented AF. Mobile single-lead ECG is more convenient to surveil cardiac rhythm with simple measurement. However, AI-enabled arrhythmia predictability by… read more here.

Keywords: ecg; lead ecg; model; single lead ... See more keywords