Studies in health technology and informatics
Apr 24, 2025
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with severe complications such as ischemic stroke and heart failure. Early detection is essential for timely intervention; however, traditional diagnostic methods often lack scalab...
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
Mar 28, 2025
AIMS: The aim of this study was to perform an external validation of an automatic machine learning (ML) algorithm for heart rhythm diagnostics using smartphone photoplethysmography (PPG) recorded by patients with atrial fibrillation (AF) and atrial f...
Nan fang yi ke da xue xue bao = Journal of Southern Medical University
Mar 20, 2025
OBJECTIVES: To design a deep learning model that balances model complexity and performance to enable its integration into wearable ECG monitoring devices for automated diagnosis of atrial fibrillation.
BACKGROUND AND AIMS: Artificial intelligence (AI) algorithms in 12-lead electrocardiogram (ECG) provides promising age prediction methods. This study investigated whether the discrepancy between ECG-derived AI-predicted age (AI-ECG age) and chronolog...
We propose a classification method for distinguishing atrial fibrillation from sinus rhythm in pulse-wave measurements obtained with a blood pressure monitor. This method combines recurrence-based plots with convolutional neural networks. Moreover, w...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Feb 25, 2025
The risk prediction of paroxysmal atrial fibrillation (PAF) is a challenge in the field of biomedical engineering. This study integrated the advantages of machine learning feature engineering and end-to-end modeling of deep learning to propose a PAF ...
Recent endeavors have led to the exploration of Machine Learning (ML) to enhance the detection and accurate diagnosis of heart pathologies. This is due to the growing need to improve efficiency in diagnostics and hasten the process of delivering trea...
BACKGROUND AND AIMS: Deep learning applied to electrocardiograms (ECG-AI) is an emerging approach for predicting atrial fibrillation or flutter (AF). This study introduces an ECG-AI model developed and tested at a tertiary cardiac centre, comparing i...
BACKGROUND: The PRAISE (PRedicting with Artificial Intelligence riSk aftEr acute coronary syndrome) score is a machine learning-based model for predicting 1-year adverse cardiovascular or bleeding events in patients with acute coronary syndrome (ACS)...
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2024
OBJECTIVE: This study aims to develop machine learning models that provide both accurate and equitable predictions of 2-year stroke risk for patients with atrial fibrillation across diverse racial groups.
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