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Artificial intelligence for atrial fibrillation detection, prediction, and treatment: A systematic review of the last decade (2013–2023)
Atrial fibrillation (AF) affects more than 30 million individuals worldwide, making it the most
prevalent cardiac arrhythmia on a global scale. This systematic review summarizes recent …
prevalent cardiac arrhythmia on a global scale. This systematic review summarizes recent …
Exploring the power of photoplethysmogram matrix for atrial fibrillation detection with integrated explainability
Atrial Fibrillation (AF) detection is paramount for cardiovascular health due to its potential
complications. In this study, we investigate the utility of Photoplethysmogram (PPG) for …
complications. In this study, we investigate the utility of Photoplethysmogram (PPG) for …
False atrial fibrillation alerts from smartwatches are associated with decreased perceived physical well-being and confidence in chronic symptoms management
KV Tran, A Filippaios, K Noorishirazi… - Cardiology and …, 2023 - pmc.ncbi.nlm.nih.gov
Wrist-based wearables have been FDA approved for AF detection. However, the health
behavior impact of false AF alerts from wearables on older patients at high risk for AF are not …
behavior impact of false AF alerts from wearables on older patients at high risk for AF are not …
Noise reduction in photoplethysmography signals using a convolutional denoising autoencoder with unconventional training scheme
Objective: We propose an efficient approach based on a convolutional denoising
autoencoder (CDA) network to reduce motion and noise artifacts (MNA) from corrupted atrial …
autoencoder (CDA) network to reduce motion and noise artifacts (MNA) from corrupted atrial …
Recent advances in the tools and techniques for AI-aided diagnosis of atrial fibrillation
Atrial fibrillation (AF) is recognized as a develo** global epidemic responsible for a
significant burden of morbidity and mortality. To counter this public health crisis, the …
significant burden of morbidity and mortality. To counter this public health crisis, the …
Recognoise: Machine-learning-based recognition of noisy segments in electrocardiogram signals
Today, wearable technology is frequently used for continuous monitoring of physiological
indicators in the health-care domain. However, mobile-health and wearable devices are …
indicators in the health-care domain. However, mobile-health and wearable devices are …
An Effective Photoplethysmography Denosing Method Based on Diffusion Probabilistic Model
Z **a, Z Luo, CH Chen, X Shen - IEEE Journal of Biomedical …, 2025 - ieeexplore.ieee.org
Photoplethysmography (PPG) is commonly used to gather health-related information but is
highly affected by motion artifacts from daily activities. Inspired by the strong denoising …
highly affected by motion artifacts from daily activities. Inspired by the strong denoising …
Smartwatch Photoplethysmogram-Based Atrial Fibrillation Detection with Premature Atrial and Ventricular Contraction Differentiation Using Densely Connected …
This study addresses the challenges of arrhythmia detection, including atrial fibrillation (AF),
using continuously collected smartwatch photoplethysmography (PPG) data. We propose a …
using continuously collected smartwatch photoplethysmography (PPG) data. We propose a …
A novel machine-learning-based noise detection method for photoplethysmography signals
Wearable devices are widespread for continuous health monitoring; capturing various
physiological parameters for remote health monitoring and early detection of health issues …
physiological parameters for remote health monitoring and early detection of health issues …
[HTML][HTML] Performance of a medical smartband with photoplethysmography technology and artificial intelligence algorithm to detect atrial fibrillation
S Blok, W Gielen, MA Piek, WF Hoeksema… - …, 2025 - pmc.ncbi.nlm.nih.gov
Background Atrial fibrillation (AF) is a prevalent arrhythmia with significant public health
implications, including increased risk of stroke and mortality. Early detection is challenging …
implications, including increased risk of stroke and mortality. Early detection is challenging …