Cardiovascular disease detection from cardiac arrhythmia ECG signals using artificial intelligence models with hyperparameters tuning methodologies
Cardiovascular disease (CVD) is connected with irregular cardiac electrical activity, which
can be seen in ECG alterations. Due to its convenience and non-invasive aspect, the ECG is …
can be seen in ECG alterations. Due to its convenience and non-invasive aspect, the ECG is …
[HTML][HTML] Machine learning based detection of T–wave alternans in real ambulatory conditions
L Pascual-Sánchez, R Goya-Esteban… - Computer Methods and …, 2024 - Elsevier
Background and objective T-wave alternans (TWA) is a fluctuation in the repolarization
morphology of the ECG. It is associated with cardiac instability and sudden cardiac death …
morphology of the ECG. It is associated with cardiac instability and sudden cardiac death …
Sig-LIME: a Signal-based Enhancement of LIME Explanation Technique
Interpreting machine learning models is facilitated by the widely employed locally
interpretable model-agnostic explanation (LIME) technique. However, when extending LIME …
interpretable model-agnostic explanation (LIME) technique. However, when extending LIME …
[HTML][HTML] Manifold analysis of the P-wave changes induced by pulmonary vein isolation during cryoballoon procedure
L Martinez-Mateu, FM Melgarejo-Meseguer… - Computers in Biology …, 2023 - Elsevier
Abstract Background/Aim: In atrial fibrillation (AF) ablation procedures, it is desirable to know
whether a proper disconnection of the pulmonary veins (PVs) was achieved. We …
whether a proper disconnection of the pulmonary veins (PVs) was achieved. We …
Классификация эпизодов нарушений сердечного ритма по информативным признакам во временной области электрокардиограммы
БК Акопян - Известия высших учебных заведений …, 2024 - pribor.elpub.ru
Аннотация Исследованы особенности классификации нарушений сердечного ритма
по сигналу одного отведения электрокардиограммы. Предложено первичное …
по сигналу одного отведения электрокардиограммы. Предложено первичное …
SPTDMD-WST: Arrhythmia classification from spatiotemporal modes of dynamic mode decomposition using wavelet scattering transform
Arrhythmia is a type of cardiovascular disease that severely alert human health. An
instantaneous monitoring of electrocardiogram signals (ECG) is an efficacious process for …
instantaneous monitoring of electrocardiogram signals (ECG) is an efficacious process for …
Exploring Cardiac Rhythms and Improving ECG Beat Classification through Latent Spaces
A Vadillo-Valderrama, J Chaquet-Ulldemolins… - IEEE …, 2024 - ieeexplore.ieee.org
In recent years, a wide variety of Machine Learning (ML) algorithms, including Deep
Learning (DL) methods, have been proposed for electrocardiogram (ECG) beat …
Learning (DL) methods, have been proposed for electrocardiogram (ECG) beat …
Advanced Ensemble Machine Learning Approach for ECG-Based Arrhythmia Detection
Cardiovascular diseases (CVDs) are the main reason causing millions of deaths around the
world. To limit the negative effects of CVDs, early arrhythmia detection is important. The …
world. To limit the negative effects of CVDs, early arrhythmia detection is important. The …
Wrist Motion Pattern Recognition from EMG Signal Processing Using Machine Learning and Neural Networks
MME Fang, RQ Fuentes-Aguilar, YY Rios… - Workshop on …, 2024 - Springer
Wrist motion pattern recognition is significant in various applications, such as human-
computer interaction and rehabilitation. This paper presents a study on wrist motion pattern …
computer interaction and rehabilitation. This paper presents a study on wrist motion pattern …
[PDF][PDF] ECG CLASSIFICATION USING DEEP LEARNING TECHNIQUES
A Henriquez - 2024 - scholarworks.calstate.edu
In the medical field, reading Electrocardiograms (ECGs) is one of the most challenging
things for physicians because of the intricate patterns and subtle abnormalities present …
things for physicians because of the intricate patterns and subtle abnormalities present …