AIMC Topic: Wavelet Analysis

Clear Filters Showing 221 to 230 of 387 articles

Uncovering the prognostic gene signatures for the improvement of risk stratification in cancers by using deep learning algorithm coupled with wavelet transform.

BMC bioinformatics
BACKGROUND: The aim of gene expression-based clinical modelling in tumorigenesis is not only to accurately predict the clinical endpoints, but also to reveal the genome characteristics for downstream analysis for the purpose of understanding the mech...

SS-SWT and SI-CNN: An Atrial Fibrillation Detection Framework for Time-Frequency ECG Signal.

Journal of healthcare engineering
Atrial fibrillation is the most common arrhythmia and is associated with high morbidity and mortality from stroke, heart failure, myocardial infarction, and cerebral thrombosis. Effective and rapid detection of atrial fibrillation is critical to redu...

EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research.

Computational and mathematical methods in medicine
In recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) signal analysis methods, using EEG signals to monitor human health has become a very popular research fi...

Recognition of Patient Groups with Sleep Related Disorders using Bio-signal Processing and Deep Learning.

Sensors (Basel, Switzerland)
Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomnography (PSG) has long been used for detection of various sleep disorders. In this research, electrocardiography (ECG) and electromayography (EMG) hav...

Analyzing the Effectiveness of the Brain-Computer Interface for Task Discerning Based on Machine Learning.

Sensors (Basel, Switzerland)
The aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using ...

A fully automated hybrid human sperm detection and classification system based on mobile-net and the performance comparison with conventional methods.

Medical & biological engineering & computing
Sperm morphology, as an indicator of fertility, is a critical tool in semen analysis. In this study, a smartphone-based hybrid system that fully automates the sperm morphological analysis is introduced with the aim of eliminating unwanted human facto...

Hyperspectral technique combined with deep learning algorithm for detection of compound heavy metals in lettuce.

Food chemistry
The aim of this research was to develop a deep learning method which involved wavelet transform (WT) and stack convolution auto encoder (SCAE) for extracting compound heavy metals detection deep features of lettuce leaves. WT was used to decompose th...

A combination of 3-D discrete wavelet transform and 3-D local binary pattern for classification of mild cognitive impairment.

BMC medical informatics and decision making
BACKGROUND: The detection of Alzheimer's Disease (AD) in its formative stages, especially in Mild Cognitive Impairments (MCI), has the potential of helping the clinicians in understanding the condition. The literature review shows that the classifica...

Optimized artificial neural network to improve the accuracy of estimated fault impedances and distances for underground distribution system.

PloS one
This paper proposes an approach to accurately estimate the impedance value of a high impedance fault (HIF) and the distance from its fault location for a distribution system. Based on the three-phase voltage and current waveforms which are monitored ...

Scalogram based prediction model for respiratory disorders using optimized convolutional neural networks.

Artificial intelligence in medicine
Auscultation of the lung is a conventional technique used for diagnosing chronic obstructive pulmonary diseases (COPDs) and lower respiratory infections and disorders in patients. In most of the earlier works, wavelet transforms or spectrograms have ...