Results 151 to 160 of about 4,872,287 (279)
Normal and tumoral melanocytes exhibit q-Gaussian random search patterns. [PDF]
da Silva PC +4 more
europepmc +1 more source
Objective The goal of this study was to determine if patient global assessment (PGA) scores reported by patients with axial spondyloarthritis (AxSpA) before the development of the AxSpA Disease Activity Score (ASDAS) can be used as a substitute for the global item of the ASDAS formula.
Connor Vershel +8 more
wiley +1 more source
A stacking based deep learning framework integrating random search neural architecture search for meniscus tear diagnosis. [PDF]
Seyyarer E, Genç H, Ayata F.
europepmc +1 more source
Random search algorithm for solving the nonlinear Fredholm integral equations of the second kind. [PDF]
Hong Z, Yan Z, Yan J.
europepmc +1 more source
Objective To characterize the prevalence and correlates of dietary supplement use, identify commonly used supplements, and evaluate potential supplement–medication interactions among adults with systemic lupus erythematosus (SLE). Methods We analyzed cross‐sectional data from 451 adults in the Approaches to Positive, Patient‐centered Experiences of ...
Sarah L. Patterson +7 more
wiley +1 more source
Sensing and decision-making in random search. [PDF]
Hein AM, McKinley SA.
europepmc +1 more source
Objective The objective of this scoping review was to synthesize evidence on the proportion of individuals living with Sjögren's disease who experience central nervous system (CNS) manifestations. Methods We searched MEDLINE (via PubMed) and Embase from 1980 through January 29, 2026, and the ECRI Guidelines Trust from 2020 through January 29, 2026 ...
Arun Varadhachary +21 more
wiley +1 more source
A stochastic neuronal model predicts random search behaviors at multiple spatial scales in C. elegans. [PDF]
Roberts WM +11 more
europepmc +1 more source
A random suffix search tree is a binary search tree constructed for the suffixes X i = 0:B i B i+1 B i+2 : : : of a sequence B 1 ; B 2 ; B 3 :; : : : of independent identically distributed random b-ary digits B j .
Ralph Neininger, Luc Devroye
core
dynoGP: Deep Gaussian Processes for Dynamic System Identification
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 +3 more
wiley +1 more source

