Results 61 to 70 of about 9,608,205 (238)

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

Replication Data for: eSLP optimization algorithm

, 2023
m-files implementing the eSLP optimization algorithm for the three simulations (3.1. - 3.3.) described in the associated paper. File README.txt contains analytical directions regarding requirements, how to verify the results and videos generated by the ...
Optimization, eSLP
core   +1 more source

Adaptive Riemannian optimization for multi-scale diffeomorphic matching

Nature Communications
Image matching is a fundamental task in quantitative biomedical and biological image analyses, enabling researchers to compare, integrate, and interpret imaging data across subjects, time points, modalities, and experimental conditions. Existing state-of-
Rohit Jena, Pratik Chaudhari, James C. Gee   +2 more
doaj   +1 more source

Research on Three-Stage and Multi-Mode Operation Optimization for Large-Scale Multi-Energy Complementary New Energy Bases

发电技术
ObjectivesIn large-scale multi-energy complementary bases, there are multiple types of resources, significant fluctuations in new energy output, complex operating conditions, and diverse demands of owners, leading to great challenges in the actual ...
YAN Xinrong, DONG Lianxin, ZHAO Dazhou, ZHENG Chenghang   +3 more
doaj   +1 more source

microRNA‐7‐5p and α‐Synuclein SAA Predict Parkinson's Disease Phenoconversion

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Corroborate blood neuron‐derived extracellular vesicle (NDEV) alpha‐synuclein (αSyn), the CSF αSyn seed amplification assay (αSyn‐SAA), and blood microRNA‐7‐5p (miR‐7‐5p) as markers for Parkinson's disease (PD) phenoconversion and determine if combining these markers would help select subjects who would be more likely to phenoconvert.
Shayan Zadegan, Praveen Velammal, Kanmani Muthiah, Madhu Jatty, Christopher Adams   +4 more
wiley   +1 more source

A variational expectation-maximization framework for balanced multi-scale learning of protein and drug interactions

Nature Communications
Protein functions are characterized by interactions with proteins, drugs, and other biomolecules. Understanding these interactions is essential for deciphering the molecular mechanisms underlying biological processes and developing new therapeutic ...
Jiahua Rao, Jiancong Xie, Qianmu Yuan, Deqin Liu, Zhen Wang, Yutong Lu, Shuangjia Zheng, Yuedong Yang   +7 more
doaj   +1 more source

Generative AI Utilization and Perspectives Among Reproductive‐Age Women with Systemic Autoimmune and Rheumatic Diseases

Arthritis Care &Research, Accepted Article.
Objective Reproductive‐age women with systemic autoimmune and rheumatic diseases (SARDs) have unique information needs related to their SARDs and reproductive health. We sought to understand their use of and receptivity to current and hypothetical generative artificial intelligence (AI) tools for health information‐seeking. Methods We conducted a cross‐
Mariam Arif, Catherine Wright, Samantha Rodriguez, Sarah Graves, Tamar Krishnamurti, Mehret Birru Talabi   +5 more
wiley   +1 more source

Coordinated Optimal Scheduling of Transmission Grid and Multi-Parks Considering Source-Load Uncertainties with Multi-Spatial–Temporal Scales

Energies
With the ongoing transformation of energy systems and the expanding scale of multi-park integrated energy systems, this paper proposes a novel multi-spatiotemporal scale scheduling framework that integrates robust optimization with distributed ...
Zhenghong Tu, Fangzong Wang, Jin Wang
doaj   +1 more source

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane, Salama Makni, Mourad Kchaou, Ahmed El Hajjaji   +3 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source