Results 141 to 150 of about 7,083,147 (335)
Utility of the APE2 Score as a Diagnostic Tool for Autoimmune Encephalitis
ABSTRACT Objective To retrospectively evaluate the diagnostic performance of the Antibody Prevalence in Epilepsy and Encephalopathy (APE2) score relative to clinician‐adjudicated autoimmune encephalitis (AE) and the Graus criteria in a tertiary neuroimmunology referral cohort, including antibody‐negative AE.
Bijoya Basu +3 more
wiley +1 more source
ABSTRACT Objective To identify inflammatory analytes in cerebrospinal fluid (CSF) and plasma associated with cognitive decline in cognitively normal (CN) older adults at risk for Alzheimer's disease (AD). Methods In a longitudinal study of 118 CN older adults (65–80 years, 54% APOE ε4, 26% preclinical AD), 1331 CSF and 1501 plasma analytes were ...
Jagan A. Pillai +13 more
wiley +1 more source
Brain-inspired, interpretable, resonant recurrent neural networks
Traditional artificial neural networks consist of nodes with nonoscillatory dynamics. Biological neural networks, on the other hand, consist of oscillatory components embedded in an oscillatory environment. Motivated by this feature of biological neurons,
Mark A. Kramer
doaj +1 more source
The UEDIN English ASR System for the IWSLT 2013 Evaluation [PDF]
This paper describes the University of Edinburgh (UEDIN) English ASR system for the IWSLT 2013 Evaluation. Notable features of the system include deep neural network acoustic models in both tandem and hybrid configuration, cross-domain adaptation with ...
Renals, Steve +5 more
core
ABSTRACT Variants in KCNA1, encoding the Kv1.1 potassium channel, cause neurological disorders including episodic ataxia and developmental and epileptic encephalopathy. We identified a novel KCNA1 variant (A401T) in a 16‐year‐old patient with autism spectrum disorder, borderline intellectual disability, and tremor, without episodic ataxia or epilepsy ...
Juan Darío Ortigoza‐Escobar +7 more
wiley +1 more source
Neural Network Models for Inflation Forecasting: An Appraisal [PDF]
We assess the power of artificial neural network models as forecasting tools for monthly inflation rates for 28 OECD countries. For short out-of-sample forecasting horizons, we find that, on average, for 45% of the countries the ANN models were a ...
Adnan Haider, Ali Choudhary
core
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
Objective Gastrointestinal (GI) involvement can lead to malnutrition in patients with systemic sclerosis (SSc). Body mass index (BMI) remains the most widely used marker to screen nutritional status. We aimed to identify predictors of lower BMI in patients with SSc. Methods Patients with SSc from a prospective US cohort meeting 2013 American College of
Ali Y. Ayla +8 more
wiley +1 more source
Interstitial lung disease (ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRDs). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the noninvasive assessment of ILD; however, its interpretation is constrained by substantial interobserver variability and the ...
Alexander Pfeil +7 more
wiley +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source

