AI Medical Compendium Topic:
Signal Processing, Computer-Assisted

Clear Filters Showing 751 to 760 of 1839 articles

Lead Reconstruction Using Artificial Neural Networks for Ambulatory ECG Acquisition.

Sensors (Basel, Switzerland)
One of the most powerful techniques to diagnose cardiovascular diseases is to analyze the electrocardiogram (ECG). To increase diagnostic sensitivity, the ECG might need to be acquired using an ambulatory system, as symptoms may occur during a patien...

Linear and non-linear feature extraction from rat electrocorticograms for seizure detection by support vector machine.

Biomedizinische Technik. Biomedical engineering
Seizures, the main symptom of epilepsy, are provoked due to a neurological disorder that underlies the disease. The accurate detection of seizures is a crucial step in any procedure of treatment. In the present study, electrocorticogram (ECoG) signal...

Uncovering structured responses of neural populations recorded from macaque monkeys with linear support vector machines.

STAR protocols
When a mammal, such as a macaque monkey, sees a complex natural image, many neurons in its visual cortex respond simultaneously. Here, we provide a protocol for studying the structure of population responses in laminar recordings with a machine learn...

Artificial Intelligence-Enabled ECG to Identify Silent Atrial Fibrillation in Embolic Stroke of Unknown Source.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Embolic strokes of unknown source (ESUS) are common and often suspected to be caused by unrecognized paroxysmal atrial fibrillation (AF). An AI-enabled ECG (AI-ECG) during sinus rhythm has been shown to identify patients with unrecognized...

Optimized adaptive Savitzky-Golay filtering algorithm based on deep learning network for absorption spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
An improved Savitzky-Golay (S-G) filtering algorithm was developed to denoise the absorption spectroscopy of nitrogen oxide (NO). A deep learning (DL) network was introduced to the traditional S-G filtering algorithm to adjust the window size and pol...

MEGnet: Automatic ICA-based artifact removal for MEG using spatiotemporal convolutional neural networks.

NeuroImage
Magnetoencephalography (MEG) is a functional neuroimaging tool that records the magnetic fields induced by neuronal activity; however, signal from non-neuronal sources can corrupt the data. Eye-blinks, saccades, and cardiac activity are three of the ...

A New Hybrid Forecasting Model Based on SW-LSTM and Wavelet Packet Decomposition: A Case Study of Oil Futures Prices.

Computational intelligence and neuroscience
The crude oil futures prices forecasting is a significant research topic for the management of the energy futures market. In order to optimize the accuracy of energy futures prices prediction, a new hybrid model is established in this paper which com...

Artificial Intelligence Analysis of EEG Amplitude in Intensive Heart Care.

Journal of healthcare engineering
This article first studied the morphological characteristics of the EEG for intensive cardiac care; that is, based on the analysis of the mechanism of disease diagnosis and treatment, a signal processing and machine learning model was constructed. Th...

Exploring the Use of Brain-Computer Interfaces in Stroke Neurorehabilitation.

BioMed research international
With the continuous development of artificial intelligence technology, "brain-computer interfaces" are gradually entering the field of medical rehabilitation. As a result, brain-computer interfaces (BCIs) have been included in many countries' strateg...

Objective pain stimulation intensity and pain sensation assessment using machine learning classification and regression based on electrodermal activity.

American journal of physiology. Regulatory, integrative and comparative physiology
An objective measure of pain remains an unmet need of people with chronic pain, estimated to be 1/3 of the adult population in the United States. The current gold standard to quantify pain is highly subjective, based upon self-reporting with numerica...