Results 111 to 120 of about 4,733,381 (248)

A Novel KCNA1 Variant in a Patient With Tremor and Autism Spectrum Disorder Causes Mixed LOF/GOF Defects of Kv1.1 Channels

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
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

A Model for Programmability and Virtuality in Dynamical Neural Networks [PDF]

open access: yes, 2009
In this dissertation a fixed-weight architecture for Continuous Time Recurrent Neural Networks (CTRNNs) is proposed in order to give an account for biological phenomena, controlled by neuronal activity, in which changes of behavior occur so fast that ...
Donnarumma, Francesco
core   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

open access: yesArthritis Care &Research, EarlyView.
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

Determinants of Body Mass Index in Early Systemic Sclerosis: Implications for Nutritional Risk Stratification

open access: yesArthritis Care &Research, EarlyView.
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

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

open access: yesArthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein   +3 more
wiley   +1 more source

Beyond Visual Scoring: Computational Computed Tomography Analysis for High‐Resolution Computed Tomography–Based Quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

open access: yesArthritis Care &Research, EarlyView.
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

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

open access: yesAdvanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora   +4 more
wiley   +1 more source

Extended LaSalle’s invariance principle for full-range cellular neural networks

open access: yes, 2008
The paper develops a Lyapunov method, which is based on a generalized version of LaSalle's invariance principle, for studying convergence and stability of the differential inclusions modeling the dynamics of the full-range (FR) model of cellular neural ...
DI MARCO M.   +3 more
core   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

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