AIMC Topic: Neural Conduction

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Advanced multiscale machine learning for nerve conduction velocity analysis.

Scientific reports Jul 2, 2025
This paper presents an advanced machine learning (ML) framework for precise nerve conduction velocity (NCV) analysis, integrating multiscale signal processing with physiologically-constrained deep learning. Our approach addresses three fundamental li...
Humans Male Signal Processing, Computer-Assisted Wavelet Analysis Neural Conduction Neural Networks, Computer Machine Learning Female
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Longitudinal artificial intelligence-based deep learning models for diagnosis and prediction of the future occurrence of polyneuropathy in diabetes and prediabetes.

Neurophysiologie clinique = Clinical neurophysiology May 18, 2024
OBJECTIVE: The objective of this study was to develop artificial intelligence-based deep learning models and assess their potential utility and accuracy in diagnosing and predicting the future occurrence of diabetic distal sensorimotor polyneuropathy...
Prediabetic State Neural Networks, Computer Diabetic Neuropathies Artificial Intelligence Deep Learning Neural Conduction Humans Male Aged Female Diabetes Mellitus, Type 2 Middle Aged Adult Longitudinal Studies
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One-Stop Automated Diagnostic System for Carpal Tunnel Syndrome in Ultrasound Images Using Deep Learning.

Ultrasound in medicine & biology Dec 3, 2023
OBJECTIVE: Ultrasound (US) examination has unique advantages in diagnosing carpal tunnel syndrome (CTS), although identification of the median nerve (MN) and diagnosis of CTS depend heavily on the expertise of examiners. In the aim of alleviating thi...
Humans Neural Conduction Carpal Tunnel Syndrome Deep Learning Ultrasonography Median Nerve
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Diagnosis of carpal tunnel syndrome using a 10-s grip-and-release test with video and machine learning analysis.

The Journal of hand surgery, European volume Nov 22, 2023
UNLABELLED: We developed a finger motion-based diagnostic system for carpal tunnel syndrome by analysing 10 second grip-and-release test videos. Using machine learning, it estimated presence of carpal tunnel syndrome (89% sensitivity and 83% specific...
Aged Adult Sensitivity and Specificity Humans Machine Learning Female Video Recording Neural Conduction Carpal Tunnel Syndrome Male Middle Aged Hand Strength
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Using deep learning for ultrasound images to diagnose carpal tunnel syndrome with high accuracy.

Ultrasound in medicine & biology Jul 20, 2022
Recently, deep learning (DL) algorithms have been adapted for the diagnosis of medical images. The purpose of this study was to detect image features using DL without measuring median nerve cross-sectional area (CSA) in ultrasonography (US) images of...
Humans Sensitivity and Specificity Deep Learning Neural Conduction Carpal Tunnel Syndrome Ultrasonography Median Nerve
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Machine learning-based approach for disease severity classification of carpal tunnel syndrome.

Scientific reports Aug 31, 2021
Identifying the severity of carpal tunnel syndrome (CTS) is essential to providing appropriate therapeutic interventions. We developed and validated machine-learning (ML) models for classifying CTS severity. Here, 1037 CTS hands with 11 variables eac...
Retrospective Studies Female Humans Machine Learning Electrodiagnosis Body Mass Index Carpal Tunnel Syndrome Pain Measurement Male Neural Conduction Middle Aged Severity of Illness Index
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A coarse-graining framework for spiking neuronal networks: from strongly-coupled conductance-based integrate-and-fire neurons to augmented systems of ODEs.

Journal of computational neuroscience Feb 16, 2019
Homogeneously structured, fluctuation-driven networks of spiking neurons can exhibit a wide variety of dynamical behaviors, ranging from homogeneity to synchrony. We extend our partitioned-ensemble average (PEA) formalism proposed in Zhang et al. (Jo...
Entropy Neural Conduction Electrophysiological Phenomena Models, Neurological Neurons Nerve Net Neural Networks, Computer Algorithms Computer Simulation Humans
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Self-organization of a recurrent network under ongoing synaptic plasticity.

Neural networks : the official journal of the International Neural Network Society Jun 5, 2014
We investigated the organization of a recurrent network under ongoing synaptic plasticity using a model of neural oscillators coupled by dynamic synapses. In this model, the coupling weights changed dynamically, depending on the timing between the os...
Neurons Synapses Neuronal Plasticity Fourier Analysis Neural Conduction Humans Models, Neurological Neural Networks, Computer Action Potentials Algorithms
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Machine learning powered tools for automated analysis of muscle sympathetic nerve activity recordings.

Physiological reports Aug 1, 2021
Automated analysis and quantification of physiological signals in clinical practice and medical research can reduce manual labor, increase efficiency, and provide more objective, reproducible results. To build a novel platform for the analysis of mus...
Sympathetic Nervous System Neural Conduction Electrodiagnosis Adolescent Muscle, Smooth, Vascular Signal-To-Noise Ratio Humans Adult Middle Aged Machine Learning Aged
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Chaos versus noise as drivers of multistability in neural networks.

Chaos (Woodbury, N.Y.) Oct 1, 2018
The multistable behavior of neural networks is actively being studied as a landmark of ongoing cerebral activity, reported in both functional Magnetic Resonance Imaging (fMRI) and electro- or magnetoencephalography recordings. This consists of a cont...
Models, Neurological Data Collection Nonlinear Dynamics Temperature Magnetic Resonance Imaging Cluster Analysis Ion Channels Synapses Neural Conduction Magnetoencephalography Stochastic Processes Neural Networks, Computer Humans Algorithms Oscillometry
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