AIMC Topic: Wavelet Analysis
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Multi-modal signal integration for enhanced sleep stage classification: Leveraging EOG and 2-channel EEG data with advanced feature extraction.
Artificial intelligence in medicine
May 2, 2025
This paper introduces an innovative approach to sleep stage classification, leveraging a multi-modal signal integration framework encompassing Electrooculography (EOG) and two-channel electroencephalography (EEG) data. We explore the utility of vario...
Unveiling fetal heart health: harnessing auto-metric graph neural networks and Hazelnut tree search for ECG-based arrhythmia detection.
Computer methods in biomechanics and biomedical engineering
Apr 24, 2025
Fetal electrocardiogram (ECG) provides a non-invasive means to assess fetal heart health, but isolating the fetal signal from the dominant maternal ECG remains challenging. This study introduces the FHH-AMGNN-HTSOA-ECG-AD method for enhanced fetal ar...
Prediction of significant congenital heart disease in infants and children using continuous wavelet transform and deep convolutional neural network with 12-lead electrocardiogram.
BMC pediatrics
Apr 24, 2025
BACKGROUND: Congenital heart disease (CHD) affects approximately 1% of newborns and is a leading cause of mortality in early childhood. Despite the importance of early detection, current screening methods, such as pulse oximetry and auscultation, hav...
CWMS-GAN: A small-sample bearing fault diagnosis method based on continuous wavelet transform and multi-size kernel attention mechanism.
PloS one
Apr 11, 2025
In industrial production, obtaining sufficient bearing fault signals is often extremely difficult, leading to a significant degradation in the performance of traditional deep learning-based fault diagnosis models. Many recent studies have shown that ...
Source-free time series domain adaptation with wavelet-based multi-scale temporal imputation.
Neural networks : the official journal of the International Neural Network Society
Apr 2, 2025
Recent works on source-free domain adaptation (SFDA) for time series reveal the effectiveness of learning domain-invariant temporal dynamics on improving the cross-domain performance of the model. However, existing SFDA methods for time series mainly...
A hybrid parallel convolutional spiking neural network for enhanced skin cancer detection.
Scientific reports
Apr 1, 2025
The most widespread kind of cancer, affecting millions of lives is skin cancer. When the condition of illness worsens, the chance of survival is reduced, and thus detection of skin cancer is extremely difficult. Hence, this paper introduces a new mod...
Multiscale analysis of heart sound signals in the wavelet domain for heart murmur detection.
Scientific reports
Mar 25, 2025
A heart murmur is an atypical sound produced by blood flow through the heart. It can indicate a serious heart condition, so detecting heart murmurs is critical for identifying and managing cardiovascular diseases. However, current methods for identif...
An ensemble approach using multidimensional convolutional neural networks in wavelet domain for schizophrenia classification from sMRI data.
Scientific reports
Mar 25, 2025
Schizophrenia is a complicated mental condition marked by disruptions in thought processes, perceptions, and emotional responses, which can cause severe impairment in everyday functioning. sMRI is a non-invasive neuroimaging technology that visualize...
Deciphering the molecular fingerprint of haemoglobin in lung cancer: A new strategy for early diagnosis using two-trace two-dimensional correlation near infrared spectroscopy (2T2D-NIRS) and machine learning techniques.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Mar 23, 2025
Lung cancer remains one of the deadliest malignancies worldwide, highlighting the need for highly sensitive and minimally invasive early diagnostic methods. Near-infrared spectroscopy (NIRS) offers unique advantages in probing molecular vibrational i...
Abnormal heart sound recognition using SVM and LSTM models in real-time mode.
Scientific reports
Mar 17, 2025
Cardiovascular diseases are non-communicable diseases that are considered the leading cause of death worldwide accounting for 17.9 million fatalities. Auscultation of heart sounds is the most common and valuable way of diagnosing heart diseases. Norm...
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