Sensor-level MEG combined with machine learning yields robust classification of mild traumatic brain injury patients-Reference-Cited by-同舟云学术

Sensor-level MEG combined with machine learning yields robust classification of mild traumatic brain injury patients

Published:2023-09 Issue: Volume:153 Page:79-87
ISSN:1388-2457
Container-title:Clinical Neurophysiology
language:en
Short-container-title:Clinical Neurophysiology

Author:

Aaltonen Juho^ORCID,Heikkinen Verna,Kaltiainen Hanna,Salmelin Riitta^ORCID,Renvall Hanna

Publisher

Elsevier BV

Subject

Physiology (medical),Neurology (clinical),Neurology,Sensory Systems

Reference52 articles.

1. Magnetoencephalography abnormalities in adult mild traumatic brain injury: A systematic review;Allen;Neuroimage Clin,2021

2. American Congress of Rehabilitation Medicine Committee on Social, Ethical and Rehabilitation, Environmental Aspects of (1993). Addressing the post-rehabilitation health care needs of persons with disabilities. Arch Phys Med Rehabil, 74(12 Spec No): S8–14.

3. Altered cross-frequency coupling in resting-state Meg after mild traumatic brain injury;Antonakakis;Int J Psychophysiol,2016

4. Altered rich-club and frequency-dependent subnetwork organization in mild traumatic brain injury: A MEG resting-state study;Antonakakis;Front Hum Neurosci,2017

5. EEG differences between eyes-closed and eyes-open resting remain in healthy ageing;Barry;Biol Psychol,2017

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1. From bench to bedside: Overview of magnetoencephalography in basic principle, signal processing, source localization and clinical applications;NeuroImage: Clinical;2024

2. Using normative modeling and machine learning for detecting mild traumatic brain injury from magnetoencephalography data;PLOS Computational Biology;2023-11-09