AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Respiration

Showing 81 to 90 of 158 articles

Clear Filters

Classification and Detection of Breathing Patterns with Wearable Sensors and Deep Learning.

Sensors (Basel, Switzerland)
Rapid assessment of breathing patterns is important for several emergency medical situations. In this research, we developed a non-invasive breathing analysis system that automatically detects different types of breathing patterns of clinical signifi...

DeepResp: Deep learning solution for respiration-induced B fluctuation artifacts in multi-slice GRE.

NeuroImage
Respiration-induced B fluctuation corrupts MRI images by inducing phase errors in k-space. A few approaches such as navigator have been proposed to correct for the artifacts at the expense of sequence modification. In this study, a new deep learning ...

Adaptive respiratory signal prediction using dual multi-layer perceptron neural networks.

Physics in medicine and biology
To improve the prediction accuracy of respiratory signals by adapting the multi-layer perceptron neural network (MLP-NN) model to changing respiratory signals. We have previously developed an MLP-NN to predict respiratory signals obtained from a real...

Emotion Assessment Using Feature Fusion and Decision Fusion Classification Based on Physiological Data: Are We There Yet?

Sensors (Basel, Switzerland)
Emotion recognition based on physiological data classification has been a topic of increasingly growing interest for more than a decade. However, there is a lack of systematic analysis in literature regarding the selection of classifiers to use, sens...

Analysis of Behavior Trajectory Based on Deep Learning in Ammonia Environment for Fish.

Sensors (Basel, Switzerland)
Ammonia can be produced by the respiration and excretion of fish during the farming process, which can affect the life of fish. In this paper, to research the behavior of fish under different ammonia concentration and make the corresponding judgment ...

Derivation of Breathing Metrics From a Photoplethysmogram at Rest: Machine Learning Methodology.

JMIR mHealth and uHealth
BACKGROUND: There has been a recent increased interest in monitoring health using wearable sensor technologies; however, few have focused on breathing. The ability to monitor breathing metrics may have indications both for general health as well as r...

Hyperparameter Optimization Method Based on Harmony Search Algorithm to Improve Performance of 1D CNN Human Respiration Pattern Recognition System.

Sensors (Basel, Switzerland)
In this study, we propose a method to find an optimal combination of hyperparameters to improve the accuracy of respiration pattern recognition in a 1D (Dimensional) convolutional neural network (CNN). The proposed method is designed to integrate wit...

Multi-channel lung sound classification with convolutional recurrent neural networks.

Computers in biology and medicine
In this paper, we present an approach for multi-channel lung sound classification, exploiting spectral, temporal and spatial information. In particular, we propose a frame-wise classification framework to process full breathing cycles of multi-channe...

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...

A multi-scale variational neural network for accelerating motion-compensated whole-heart 3D coronary MR angiography.

Magnetic resonance imaging
PURPOSE: To enable fast reconstruction of undersampled motion-compensated whole-heart 3D coronary magnetic resonance angiography (CMRA) by learning a multi-scale variational neural network (MS-VNN) which allows the acquisition of high-quality 1.2 × 1...