Results 61 to 70 of about 29,334,281 (289)

Subclinical Optic Nerve Involvement in Radiologically Isolated Syndrome: Multimodal Detection and Diagnostic Impact

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We aimed to determine the frequency of subclinical optic nerve (ON) lesions using MRI, optical coherence tomography (OCT), and visual evoked potentials (VEP) in radiologically isolated syndrome (RIS), and to assess their diagnostic and prognostic significance.
Christine Lebrun‐Frenay   +13 more
wiley   +1 more source

Family income trajectory during childhood is associated with adiposity in adolescence: a latent class growth analysis [PDF]

open access: yesBMC Public Health, 2012
Childhood socioeconomic disadvantage has been linked with obesity in cross-sectional research, although less is known about how changes in socioeconomic status influence the development of obesity. Researchers have hypothesized that upward socioeconomic mobility may attenuate the health effects of earlier socioeconomic disadvantage; while downward ...
Kendzor Darla E   +2 more
openaire   +3 more sources

Latent Class Analysis—Fit statistics.

open access: yes, 2023
Latent Class Analysis—Fit statistics.
Mara Soncin (12996734)   +3 more
core   +1 more source

Myostatin/Smad3 in Spinal Muscular Atrophy: Biomarkers of Disease Severity and Treatment Response

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Given the role of Myostatin (MSTN) in muscle homeostasis and its modulation by current spinal muscular atrophy (SMA) therapies, we investigated serum MSTN and, for the first time, its downstream effector Smad3 as candidate non‐invasive biomarkers in SMA patients undergoing disease‐modifying therapies (DMTs).
Giorgia Riolo   +11 more
wiley   +1 more source

Recovery Trajectories of Executive Functioning After Pediatric TBI: A Latent Class Growth Modeling Analysis [PDF]

open access: yesJournal of Head Trauma Rehabilitation, 2017
Objective: To identify latent trajectories of executive functioning (EF) recovery overtime after childhood traumatic brain injury (TBI) and examine the predictive value of known risk factors within and across recovery trajectories using latent class growth modeling (LCGM). Method: A
Megan E, Narad   +6 more
openaire   +2 more sources

Patients improve, patterns persist: longitudinal stability of RA joint involvement patterns

open access: yesArthritis Care &Research, Accepted Article.
Objective Rheumatoid arthritis is a heterogeneous disease. Data‐driven approaches, from synovial histology to joint involvement patterns (JIPs), have sought to define clinically meaningful subgroups. Whether these subgroups represent stable phenotypes or transient disease states remains unclear.
Tjardo Maarseveen   +24 more
wiley   +1 more source

Adolescent determinants of life-course leisure-time vigorous physical activity trajectories: a 27-Year longitudinal study

open access: yesBMC Public Health, 2023
Background Adolescence is regarded as formative years for building the foundations for life-long health and well-being, and adolescent determinants of physical activity (PA) development is particularly interesting.
Frida Kathrine Sofie Mathisen   +3 more
doaj   +1 more source

Building Latent Class Growth Trees [PDF]

open access: yes, 2017
Researchers use latent class growth (LCG) analysis to detect meaningful subpopulations that display different growth curves. However, especially when the number of classes required to obtain a good fit is large, interpretation of the encountered class ...
Van Den Bergh, Mattis   +3 more
core   +1 more source

Class proportions and class-specific probabilities from a four-latent-class model of chronic conditions.

open access: yes, 2022
Class proportions and class-specific probabilities from a four-latent-class model of chronic conditions.
Katherine Keenan (543406)   +4 more
core   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational 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   +3 more
wiley   +1 more source

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