Characterizing Cutaneous α‐Synuclein Deposition and Seeding Activity in Parkinson's Disease Subtypes
ABSTRACT Objective Cutaneous phosphorylated α‐synuclein (p‐syn) and α‐synuclein seeding activity are promising biomarkers for Parkinson's disease (PD), but their clinical value remains uncertain due to disease heterogeneity. This study evaluates these two biomarkers in PD patients to inform phenotype‐specific diagnosis and disease severity assessment ...
Yuting Jin +8 more
wiley +1 more source
An automated extraction of spectral-temporal and spatial-temporal features of EEG for emotion detection. [PDF]
Islam M, Lee T.
europepmc +1 more source
ABSTRACT Objective To evaluate the expression of nine blood RNA biomarkers in a clinical trial based on genes previously identified in an experimental monkey model of stroke for diagnosis feasibility and prognostication. Methods IBIS‐CT1 was a prospective longitudinal study enrolling patients with ischemic stroke (IS) or intracerebral hemorrhage (ICH ...
Salomé Retailleau +11 more
wiley +1 more source
Convolutional Neural Network Models Leverage Morphological Rather Than Temporal Features to Detect Myocardial Diseases From 12-Lead Electrocardiograms. [PDF]
Nakayama M +6 more
europepmc +1 more source
ABSTRACT Objective To determine whether myelin‐sensitive quantitative MRI reveals microstructural abnormalities in normal‐appearing cortex (NACtx) in myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD), indicating that conventional MRI underestimates remission residual cortical injury.
Valentina Camera +20 more
wiley +1 more source
Enhanced multi objective graph learning approach for optimizing traffic speed prediction on spatial and temporal features. [PDF]
Karthika B, Uma Maheswari N.
europepmc +1 more source
Temporal features of concepts are grounded in time perception neural networks: An EEG study. [PDF]
Johari K, Lai VT, Riccardi N, Desai RH.
europepmc +1 more source
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
Lightweight machine learning framework using temporal features for electric vehicle demand response forecasting on edge devices. [PDF]
Durrani AM +8 more
europepmc +1 more source
Exploring Tactile Temporal Features for Object Pose Estimation during Robotic Manipulation. [PDF]
Galaiya VR +4 more
europepmc +1 more source

