Results 61 to 70 of about 8,669,620 (261)

Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani   +10 more
wiley   +1 more source

Quantitative MRI Uncovers Subtle Cortical Damage in Myelin Oligodendrocyte Glycoprotein Antibody‐Associated Disease

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

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

open access: yesAnnals 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

Optimizing deep reinforcement learning process by applying transfer learning. [PDF]

open access: yes, 2020
Optimizing Deep Reinforcement Learning Process by Applying Transfer Learning. In this thesis we try to apply transfer learning to deep reinforcement learning, to optimize and speed up the learning process of an agent.
Jakimčikas, Martynas,
core  

CSF Cytokine Network Organization Predicts Progression Independent of Relapse and MRI Activity in Multiple Sclerosis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Progression independent of relapse activity is a major determinant of long‐term disability in multiple sclerosis, but its immunopathologic basis remains incompletely understood. We investigated whether relapse‐independent progression in radiologically stable relapsing–remitting multiple sclerosis is associated with distinct ...
Antonio Bruno   +19 more
wiley   +1 more source

Boundary‐Dependent Sleep–Wake Dysregulation in Idiopathic Hypersomnia

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Idiopathic hypersomnia (IH) presents with excessive daytime sleepiness (EDS) despite apparently preserved nocturnal sleep, challenging traditional models of hypersomnolence based on sleep loss or fragmentation. We aimed to test the hypothesis that EDS in IH reflects excessive stabilization of the sleep state, consistent with ...
Samantha Mombelli   +13 more
wiley   +1 more source

Quality of service optimization algorithm based on deep reinforcement learning in software defined network

open access: yes物联网学报, 2023
Deep reinforcement learning has strong abilities of decision-making and generalization and often applies to the quality of service (QoS) optimization in software defined network (SDN).However, traditional deep reinforcement learning algorithms have ...
Cenhuishan LIAO   +4 more
doaj   +2 more sources

Deep Reinforcement Learning Approach for Traffic Light Control and Transit Priority

open access: yesFuture Transportation
This study investigates the use of deep reinforcement learning techniques to improve traffic signal control systems through the integration of deep learning and reinforcement learning approaches.
Saeed Mansouryar   +3 more
doaj   +1 more source

Review of Deep Reinforcement Learning-Based Object Grasping: Techniques, Open Challenges, and Recommendations

open access: yesIEEE Access, 2020
The motivation behind our work is to review and analyze the most relevant studies on deep reinforcement learning-based object manipulation. Various studies are examined through a survey of existing literature and investigation of various aspects, namely,
Marwan Qaid Mohammed   +2 more
doaj   +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

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