Results 31 to 40 of about 207,837 (263)
Applied Sciences, 2020 The main goal of any classification or regression task is to obtain a model that will generalize well on new, previously unseen data. Due to the recent rise of deep learning and many state-of-the-art results obtained with deep models, deep learning ...
Ivana Marin +2 more
doaj +1 more source
Deep Adversarial Reinforcement Learning With Noise Compensation by Autoencoder
IEEE Access, 2021 We present a new adversarial learning method for deep reinforcement learning (DRL). Based on this method, robust internal representation in a deep Q-network (DQN) was introduced by applying adversarial noise to disturb the DQN policy; however, it was ...
Kohei Ohashi +4 more
doaj +1 more source
FEBS Open Bio, EarlyView.Biophysical characterisation shows that NanX, a membrane transport protein from the major facilitator superfamily (MFS), forms both monomers and dimers after purification. AlphaFold modelling and substrate docking provide information on residues likely involved in substrate recognition for NanX and another MFS member, NanT.
Michael C. Newton‐Vesty +13 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit +11 more
wiley +1 more source
Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang +4 more
wiley +1 more source
, 2014 The stable solution of ill-posed non-linear operator equations in Banach space requires regularization. One important approach is based on Tikhonov regularization, in which case a one-parameter family of regularized solutions is obtained.
Anzengruber, Stephan W. +2 more
core +1 more source
A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Arterial Spin‐Labeling MRI at the Cortical‐CSF Interface: A Novel Biomarker in Alzheimer Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background/Objective Arterial spin‐labeling (ASL) MRI can measure perfusion signal adjacent to CSF spaces and may provide information regarding CSF‐adjacent water transport physiology. We developed an automated pipeline to extract cortical‐CSF interface (IF) perfusion for comparison between Alzheimer disease (AD) and cognitively normal ...
Mona Asghariahmadabad +22 more
wiley +1 more source
Системный анализ и прикладная информатика, 2017 The statistical maximum likelihood (EM) method and the algebraic reconstruction method with simultaneous iterations (SART) are two methods of iterative tomographic reconstruction.
S. A. Zolotarev +2 more
doaj +1 more source
Mathematics, 2021 Over the last decade, regularized regression methods have offered alternatives for performing multi-marker analysis and feature selection in a whole genome context.
Juan C. Laria +8 more
doaj +1 more source