Results 171 to 180 of about 788,437 (264)

Cognitive Behavioral Therapy for Youth with Childhood‐Onset Lupus: A Randomized Clinical Trial

Arthritis Care &Research, Accepted Article.
Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist.
Natoshia R. Cunningham, Thea Senger‐Carpenter, Jocelyn Zuckerman, Michelle Adler, Mallet R. Reid, Ashley Danguecan, Luana Flores Pereira, Sarah I. Mossad, Samantha L. Ely, Khalid Abulaban, Elizabeth A. Kessler, Natalie Rosenwasser, Tamar B. Rubinstein, Ekemini A. Ogbu, Emily A. Smitherman, Alaina Miller, Taylor Abounader, Elizabeth Ross, Livie Timmerman, Dhriti Sharma, Jennifer N. Stinson, Stacy Allen, Kabita Nanda, Tala El Tal, Deborah M. Levy, Linda T. Hiraki, Hermine I. Brunner, Mathew Reeves, Steven J. Pierce, Andrea Knight   +29 more
wiley   +1 more source

Music genre classification with modified residual learning and dual neural network. [PDF]

PLoS One
Ashraf M, Abid F, Raza MO, Rasheed J, Alsubai S, Asuroglu T.   +5 more
europepmc   +1 more source

Deep residual learning for neuroimaging: An application to predict progression to Alzheimer's disease. [PDF]

J Neurosci Methods, 2020
Abrol A, Bhattarai M, Fedorov A, Du Y, Plis S, Calhoun V, Alzheimer’s Disease Neuroimaging Initiative.   +6 more
europepmc   +1 more source

Evaluation of a novel EHR sidecar application to display RA clinical outcomes during clinic visits: results of a stepped‐wedge cluster randomized pragmatic trial

Arthritis Care &Research, Accepted Article.
Objective We developed a novel EHR sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk, Jing Li, Cathy Nasrallah, Cherish Wilson, Alicia Hamblin, Christine Hariz, Cammie Young, Stephen Shiboski, Emma Kersey, Mary Nakamura, Judith F. Ashouri, Mehrdad Matloubian, Andrew J. Gross, Jennifer Barton, Beth Berrean, Jonathan Prugh, Jinoos Yazdany   +16 more
wiley   +1 more source

Image-text guided fundus vessel segmentation via attention mechanism and gated residual learning. [PDF]

Front Cell Dev Biol
Xu J, Liu Q, Shen J, Tan R, Tian S, Chi W, Yang W.   +6 more
europepmc   +1 more source

Denoising of 3D Brain MR Images with Parallel Residual Learning of Convolutional Neural Network Using Global and Local Feature Extraction. [PDF]

Comput Intell Neurosci, 2021
Wu L, Hu S, Liu C.
europepmc   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source

Physics-informed residual learning with spatiotemporal local support for inverse ECG reconstruction. [PDF]

Sci Rep
Zhu L, Bilchick K, Xie J.
europepmc   +1 more source

Artificial Residual Noise in Machine Learning

, 2022
Innen området for digital etterforskning av lyd har det vært en viss skepsis til bruken av maskinlæringsmodeller i forbindelse med fjerning av bakgrunnsstøy. Selv om støydemping ved hjelp av maskinlæring kan gi både effektivitet og hjelpe til med å håndtere mengden data som en etterforsker vil stå overfor, har det ikke blitt tatt i bruk som en ...
openaire   +1 more source