Results 41 to 50 of about 4,458,250 (263)

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

Maximum kernel likelihood estimation [PDF]

, 2008
We introduce an estimator for the population mean based on maximizing likelihoods formed by parameterizing a kernel density estimate. Due to these origins, we have dubbed the estimator the maximum kernel likelihood estimate (mkle). A speedy computational
Jaki, Thomas, West, R. Webster
core   +4 more sources

Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias, Federica Avantaggiato, Gianni Pezzoli, Andrea Canessa   +3 more
wiley   +1 more source

Temporal adaptive kernel density estimation for short-term uncertainty modeling of renewable energy generation

International Journal of Electrical Power & Energy Systems
Kernel density estimation (KDE) is widely employed to analyze the short-term uncertainty associated with renewable energy generation in power systems, owing to its ability to estimate probability density functions without prior distribution assumptions ...
Xiao Yang, Tian-Tian Yu, Shichang Cui, Guokai Hao, Fei Hu   +4 more
doaj   +1 more source

Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay, Merve Alaylioglu, Erdi Sahin, Sanem Sultan Yoruk Oner, Gulce Iskan, Gulce Cosku Yilmaz Cakan, Gozde Kizilates‐Evin, Emre Hari, Elif Kurt, Erdinc Dursun, Basar Bilgic, Hasmet Hanagasi, Hakan Gurvit, Tamer Demiralp, Duygu Gezen‐Ak, Bedia Samanci   +15 more
wiley   +1 more source

Density estimation and adaptive bandwidths: A primer for public health practitioners

International Journal of Health Geographics, 2010
Background Geographic information systems have advanced the ability to both visualize and analyze point data. While point-based maps can be aggregated to differing areal units and examined at varying resolutions, two problems arise 1) the modifiable ...
Tanski Susanne, Sargent James, Shi Xun, Carlos Heather A, Berke Ethan M   +4 more
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

SD-KDE: Score-Debiased Kernel Density Estimation

ICLR 2025 Workshop on Frontiers of Probabilistic ...
Epstein, Elliot L., Dwaraknath, Rajat, Sornwanee, Thanawat, Winnicki, John, Liu, Jerry Weihong   +4 more
openaire   +2 more sources

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella, Veria Vacchiano, Vittorio Velucci, Stefano Zoccolella, Rocco Liguori, Giovanni Defazio   +5 more
wiley   +1 more source

Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC [PDF]

Kernel density estimation for multivariate data is an important technique that has a wide range of applications in econometrics and finance. However, it has received significantly less attention than its univariate counterpart.
Maxwell L. King,, Rob L. Hyndman, Xibin Zhang   +2 more
core   +2 more sources