Results 271 to 280 of about 1,500,611 (328)
Trajectories of Physical Function in Canadian Children With Juvenile Idiopathic Arthritis
Objective We describe trajectories of physical function in children newly diagnosed with juvenile idiopathic arthritis (JIA) and identify trajectories with persisting functional impairments and associated baseline characteristics. Methods We included patients enrolled in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry ...
Clare Cunningham +81 more
wiley +1 more source
Enhanced Range Resolution Beamforming for Subarray-Based FDA. [PDF]
Wang A, Lu Y, Xu Y.
europepmc +1 more source
Enhanced diagnosis of diabetic retinopathy: integrating advanced algorithms for automated detection and classification. [PDF]
Murali E +4 more
europepmc +1 more source
Extending GroupStruct2: a Bayesian and machine-learning framework for testing taxonomic hypotheses using morphometric data. [PDF]
Chan KO, Grismer LL.
europepmc +1 more source
Modeling insurance claims using Bayesian nonparametric regression. [PDF]
Shams M, Ghosh K.
europepmc +1 more source
EV-Planner: a machine learning approach to electric vehicle charging infrastructure planning. [PDF]
Anand B, Grama A.
europepmc +1 more source
Dynamic Path Analysis And Model Based Clustering Of Microarray Data
Matthías Kormáksson
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Model-Based Clustering with Nested Gaussian Clusters
Journal of Classification, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jason Hou-Liu, Ryan P. Browne
openaire +2 more sources
2020
Finite mixture models are being commonly used in a wide range of applications in practice concerning density estimation and clustering. An attractive feature of this approach to clustering is that it provides a sound statistical framework in which to assess the important question of how many clusters there are in the data and their validity.
McLachlan, G. J. +2 more
openaire +3 more sources
Finite mixture models are being commonly used in a wide range of applications in practice concerning density estimation and clustering. An attractive feature of this approach to clustering is that it provides a sound statistical framework in which to assess the important question of how many clusters there are in the data and their validity.
McLachlan, G. J. +2 more
openaire +3 more sources

