Results 81 to 90 of about 34,803,504 (287)

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, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

Application of deep reinforcement learning in the design and optimization of English continuing education teaching content

Discover Artificial Intelligence
This study discusses the application of deep reinforcement learning in the design and optimization of English continuing education teaching content. Aiming at the one-size-fits-all problem in the traditional education model, it puts forward personalized ...
Jinfeng Ma
doaj   +1 more source

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

Annals 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, Matteo Conti, Ettore Dolcetti, Federica Azzolini, Angela Borrelli, Roberta Fantozzi, Mario Stampanoni Bassi, Giovanni Galifi, Giuseppe Maccarrone, Luca Montaguti, Marco Cervigni, Maddalena Dal Pozzo, Roberto Furlan, Annamaria Finardi, Girolama Alessandra Marfia, Marco Salvetti, Antonella Conte, Fabio Buttari, Diego Centonze, Luana Gilio   +19 more
wiley   +1 more source

Boundary‐Dependent Sleep–Wake Dysregulation in Idiopathic Hypersomnia

Annals 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, Karine Lacourse, Hélène Blais, Anne‐Sophie Deshaies‐Rugama, Cynthia Thompson, Alex Desautels, Jacques Montplaisir, Milan Nigam, Christophe Moderie, Boshra Khajehpiri, Catherine Duclos, Jean Marc Lina, Julie Carrier, Nadia Gosselin   +13 more
wiley   +1 more source

Model-based Reinforcement Learning and the Eluder Dimension

CoRR, 2014
We consider the problem of learning to optimize an unknown Markov decision process (MDP). We show that, if the MDP can be parameterized within some known function class, we can obtain regret bounds that scale with the dimensionality, rather than cardinality, of the system.
Ian Osband, Benjamin Van Roy
openaire   +4 more sources

Adaptive Discretization for Model-Based Reinforcement Learning

CoRR, 2020
We introduce the technique of adaptive discretization to design an efficient model-based episodic reinforcement learning algorithm in large (potentially continuous) state-action spaces. Our algorithm is based on optimistic one-step value iteration extended to maintain an adaptive discretization of the space.
Sean R. Sinclair, Tianyu Wang, Gauri Jain, Siddhartha Banerjee, Christina Lee Yu   +4 more
openaire   +4 more sources

The Association of Physical Function With Psychosocial Patient‐Reported Outcomes in People With Systemic Lupus Erythematosus

Arthritis Care &Research, EarlyView.
Objective To evaluate how modifiable psychosocial factors and fatigue relate to physical functioning in patients with systemic lupus erythematosus (SLE). Methods In this cross‐sectional study of two demographically distinct cohorts (Approaches to Positive, Patient‐Centered Experiences of Aging with Lupus [APPEAL] and California Lupus Epidemiology Study
Mrinalini Dey, Jessica Fitzpatrick, Maria Dall'Era, Charmayne Dunlop‐Thomas, Courtney Hoge, S. Sam Lim, Patricia P. Katz, Jinoos Yazdany, Laura C. Plantinga   +8 more
wiley   +1 more source

Refinement of biologically inspired models of reinforcement learning [PDF]

, 2010
Reinforcement learning occurs when organisms adapt the propensities of given behaviours on the basis of associations with reward and punishment. Currently, reinforcement learning models have been validated in minimalist environments in which only 1-2 ...
Aquili, Luca
core   +2 more sources

Data-Efficient Reinforcement Learning Framework for Autonomous Flight Based on Real-World Flight Data

Drones
Recently, autonomous flight has emerged as a key technology in the aerospace and defense sectors; however, traditional code-based autonomous flight systems face limitations in complex environments.
Uicheon Lee, Seonah Lee, Kyonghoon Kim
doaj   +1 more source

Short-Term Load Forecasting Algorithm Using a Similar Day Selection Method Based on Reinforcement Learning

Energies, 2020
Short-term load forecasting (STLF) is very important for planning and operating power systems and markets. Various algorithms have been developed for STLF.
Rae-Jun Park, Kyung-Bin Song, Bo-Sung Kwon   +2 more
doaj   +1 more source