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Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu +7 more
wiley +1 more source

Short-term load forecasting using a two-stage CPO-PSO hyperparameter optimization of LSSVM. [PDF]

Sci Rep
Zhang X.
europepmc +1 more source

Short-term electric load forecasting in microgrids: Issues and challenges

, 2018
This paper compares performance of three well-known short-term load forecasting (STLF) methodologies in microgrid applications. The chosen methods include: I) seasonal auto-regressive integrated moving average with exogenous variables, ii) neural ...
Kianoush Emami (9794627) +3 more
core

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
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

Deep residual networks for short-term load forecasting: an empirical study on the impact of network depth. [PDF]

Sci Rep
Liu J +4 more
europepmc +1 more source

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian +6 more
wiley +1 more source

Loss functions in deep residual networks for short-term load forecasting: a systematic analysis. [PDF]

Sci Rep
Liu J +4 more
europepmc +1 more source

Diabetes‐Associated Cognitive Impairment: Pathophysiology and Emerging Therapies

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Diabetes‐associated cognitive impairment (DACI) is a common yet underrecognized condition, manifesting along a spectrum from mild cognitive impairment to dementia. DACI encompasses patients who develop vascular dementia (VaD) or Alzheimer's disease (AD) with diabetes as a risk factor; however, in certain patients, particularly those lacking ...
Osman Corbali +4 more
wiley +1 more source

Short-term load forecasting using a metaheuristic optimized temporal fusion transformer with decomposition technique. [PDF]

Front Artif Intell
Chandrasekaran R, Paramasivan SK.
europepmc +1 more source

Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay +15 more
wiley +1 more source

short-term load forecasting
load forecasting
artificial neural network

convolutional neural network
neural network