AI Medical Compendium Topic:
Signal Processing, Computer-Assisted

Clear Filters Showing 1131 to 1140 of 1883 articles

A deep learning-based decision support system for diagnosis of OSAS using PTT signals.

Medical hypotheses
Sleep disorders, which negatively affect an individual's daily quality of life, are a common problem for most of society. The most dangerous sleep disorder is obstructive sleep apnea syndrome (OSAS), which manifests itself during sleep and can cause ...

Latent Phase Detection of Hypoxic-Ischemic Spike Transients in the EEG of Preterm Fetal Sheep Using Reverse Biorthogonal Wavelets & Fuzzy Classifier.

International journal of neural systems
Hypoxic-ischemic (HI) studies in preterms lack reliable prognostic biomarkers for diagnostic tests of HI encephalopathy (HIE). Our group's observations from fetal sheep models suggest that potential biomarkers of HIE in the form of developing HI mic...

Automated detection of sleep apnea using sparse residual entropy features with various dictionaries extracted from heart rate and EDR signals.

Computers in biology and medicine
Sleep is a prominent physiological activity in our daily life. Sleep apnea is the category of sleep disorder during which the breathing of the person diminishes causing the alternation in the upper airway resistance. The electrocardiogram derived res...

Patient-Specific Seizure Detection Method using Hybrid Classifier with Optimized Electrodes.

Journal of medical systems
In this paper the EEG signal is analyzed by reconstructing the time series EEG signal in High dimensional Phase Space. The computational complexity in higher dimension is reduced by Principal Component Analysis for the High dimensional Phase Space ou...

Counteracting Electrode Shifts in Upper-Limb Prosthesis Control via Transfer Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Research on machine learning approaches for upper-limb prosthesis control has shown impressive progress. However, translating these results from the lab to patient's everyday lives remains a challenge because advanced control schemes tend to break do...

Deep-learning augmented RNA-seq analysis of transcript splicing.

Nature methods
A major limitation of RNA sequencing (RNA-seq) analysis of alternative splicing is its reliance on high sequencing coverage. We report DARTS (https://github.com/Xinglab/DARTS), a computational framework that integrates deep-learning-based predictions...

Semisupervised Deep Stacking Network with Adaptive Learning Rate Strategy for Motor Imagery EEG Recognition.

Neural computation
Practical motor imagery electroencephalogram (EEG) data-based applications are limited by the waste of unlabeled samples in supervised learning and excessive time consumption in the pretraining period. A semisupervised deep stacking network with an a...

Automatic Sleep Staging Employing Convolutional Neural Networks and Cortical Connectivity Images.

IEEE transactions on neural networks and learning systems
Understanding of the neuroscientific sleep mechanisms is associated with mental/cognitive and physical well-being and pathological conditions. A prerequisite for further analysis is the identification of the sleep macroarchitecture through manual sle...

Beamforming and Speckle Reduction Using Neural Networks.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
With traditional beamforming methods, ultrasound B-mode images contain speckle noise caused by the random interference of subresolution scatterers. In this paper, we present a framework for using neural networks to beamform ultrasound channel signals...