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Automated extraction of post-stroke functional outcomes from unstructured electronic health records.
Eur Stroke J
January 2025
Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA.
Purpose: Population level tracking of post-stroke functional outcomes is critical to guide interventions that reduce the burden of stroke-related disability. However, functional outcomes are often missing or documented in unstructured notes. We developed a natural language processing (NLP) model that reads electronic health records (EHR) notes to automatically determine the modified Rankin Scale (mRS).
View Article and Find Full Text PDFThe effect of repetitive and Deep Transcranial Magnetic Stimulation on quantitative electroencephalography in major depressive disorder.
Front Psychiatry
January 2025
Department of Psychiatry, Kemal Arıkan Psychiatry Clinic, Istanbul, Türkiye.
Background: F-8-coil repetitive transcranial magnetic stimulation (rTMS) and H-1-coil deep repetitive transcranial magnetic stimulation (dTMS) have been indicated for the treatment of major depressive disorder (MDD) in adult patients by applying different treatment protocols. Nevertheless, the evidence for long-term electrophysiological alterations in the cortex following prolonged TMS interventions, as assessed by quantitative electroencephalography (qEEG), remains insufficiently explored. This study aims to demonstrate the qEEG-based distinctions between rTMS and dTMS in the management of depression and to evaluate the potential correlation between the electrophysiological changes induced by these two distinct TMS interventions and the clinical improvement in depressive and anxiety symptoms.
View Article and Find Full Text PDFOverexpression of FTO alleviates traumatic brain injury induced posttraumatic epilepsy by upregulating NR4A2 expression via m6A demethylation.
Funct Integr Genomics
January 2025
Department of Radiology, The Second Xiangya Hospital of Central South University, No. 139, Renmin Middle Road, Furong District, Changsha City, Hunan Province, 410011, China.
Post-traumatic epilepsy (PTE) is a debilitating chronic outcome of traumatic brain injury (TBI). Although FTO has been reported as a possible intervention target of TBI, its precise roles in the PTE remain incompletely understood. Here we used mild or serious mice TBI model to probe the role and molecular mechanism of FTO in PTE.
View Article and Find Full Text PDFPrecision data-driven modeling of cortical dynamics reveals person-specific mechanisms underpinning brain electrophysiology.
Proc Natl Acad Sci U S A
January 2025
Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130.
Task-free brain activity affords unique insight into the functional structure of brain network dynamics and has been used to identify neural markers of individual differences. In this work, we present an algorithmic optimization framework that directly inverts and parameterizes brain-wide dynamical-systems models involving hundreds of interacting neural populations, from single-subject M/EEG time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions.
View Article and Find Full Text PDFParallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification.
PLoS One
January 2025
School of Electronics Engineering (SENSE), Vellore Institute of Technology, Vellore, Tamil Nadu, India.
In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, decoding EEG signals poses significant challenges due to their complexity, dynamic nature, and low signal-to-noise ratio (SNR). Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation.
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