Electrocardiogram pattern recognition and analysis based on artificial neural networks and support vector machines: a review
Computer systems for Electrocardiogram (ECG) analysis support the clinician in tedious
tasks (eg, Holter ECG monitored in Intensive Care Units) or in prompt detection of …
tasks (eg, Holter ECG monitored in Intensive Care Units) or in prompt detection of …
DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine
Recent global developments underscore the prominent role big data have in modern
medical science. But privacy issues constitute a prevalent problem for collecting and sharing …
medical science. But privacy issues constitute a prevalent problem for collecting and sharing …
Semisupervised ECG ventricular beat classification with novelty detection based on switching Kalman filters
Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG)
signals remains a challenge. As long-term ECG recordings continue to increase in …
signals remains a challenge. As long-term ECG recordings continue to increase in …
Cardiogan: Attentive generative adversarial network with dual discriminators for synthesis of ecg from ppg
Electrocardiogram (ECG) is the electrical measurement of cardiac activity, whereas
Photoplethysmogram (PPG) is the optical measurement of volumetric changes in blood …
Photoplethysmogram (PPG) is the optical measurement of volumetric changes in blood …
Non-invasive fetal monitoring: A maternal surface ECG electrode placement-based novel approach for optimization of adaptive filter control parameters using the LMS …
This paper is focused on the design, implementation and verification of a novel method for
the optimization of the control parameters (such as step size μ and filter order N) of LMS and …
the optimization of the control parameters (such as step size μ and filter order N) of LMS and …
Synthetic data in healthcare
Synthetic data are becoming a critical tool for building artificially intelligent systems.
Simulators provide a way of generating data systematically and at scale. These data can …
Simulators provide a way of generating data systematically and at scale. These data can …
[HTML][HTML] Quantum conditional generative adversarial network based on patch method for abnormal electrocardiogram generation
Z Qu, W Shi, P Tiwari - Computers in Biology and Medicine, 2023 - Elsevier
To address the scarcity and class imbalance of abnormal electrocardiogram (ECG)
databases, which are crucial in AI-driven diagnostic tools for potential cardiovascular …
databases, which are crucial in AI-driven diagnostic tools for potential cardiovascular …
ECG-guided non-invasive estimation of pulmonary congestion in patients with heart failure
A Raghu, D Schlesinger, E Pomerantsev… - Scientific Reports, 2023 - nature.com
Quantifying hemodynamic severity in patients with heart failure (HF) is an integral part of
clinical care. A key indicator of hemodynamic severity is the mean Pulmonary Capillary …
clinical care. A key indicator of hemodynamic severity is the mean Pulmonary Capillary …
Robust reconstruction of electrocardiogram using photoplethysmography: A subject-based Model
Electrocardiography and photoplethysmography are non-invasive techniques that measure
signals from the cardiovascular system. While the cycles of the two measurements are highly …
signals from the cardiovascular system. While the cycles of the two measurements are highly …
Synthetic PPG generation from haemodynamic model with baroreflex autoregulation: a Digital twin of cardiovascular system
Synthetic data generation has recently emerged as a substitution technique for handling the
problem of bulk data needed in training machine learning algorithms. Healthcare, primarily …
problem of bulk data needed in training machine learning algorithms. Healthcare, primarily …