A5078509307- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Bayesian Methods and Mixture Models
- Advanced Neuroimaging Techniques and Applications
- Advanced Statistical Methods and Models
- Statistical Distribution Estimation and Applications
- Palliative Care and End-of-Life Issues
- Fault Detection and Control Systems
- Probabilistic and Robust Engineering Design
- Functional Brain Connectivity Studies
- Probability and Risk Models
- Health Systems, Economic Evaluations, Quality of Life
- Advanced Neural Network Applications
- Tensor decomposition and applications
- Gene expression and cancer classification
- Domain Adaptation and Few-Shot Learning
- Neuroendocrine regulation and behavior
- Genetic Neurodegenerative Diseases
- Fibromyalgia and Chronic Fatigue Syndrome Research
- Cancer-related cognitive impairment studies
- Tryptophan and brain disorders
- Geriatric Care and Nursing Homes
- Context-Aware Activity Recognition Systems
- Evolutionary Psychology and Human Behavior
- Advanced Causal Inference Techniques
Biogen (United States)
2017-2022
University of Florida
2015-2017
Cancer Research And Biostatistics
2017
Institute on Aging
2016
Florida College
2015-2016
New York University
2013-2014
Columbia University
2010-2013
University of Science and Technology of China
2007-2008
Objective Slowly expanding lesions (SELs), a subgroup of chronic white matter that gradually expand over time, have been shown to predict disability accumulation in primary progressive multiple sclerosis (MS) disease. However, the relationships between SELs, acute lesion activity (ALA), overall (CLA) and progression are not well understood. In this study, we examined ASCEND phase III clinical trial, which compared natalizumab with placebo secondary MS (SPMS). Methods Patients complete...
Background . Chronic pain is associated with increased morbidity and mortality, predominated by cardiovascular disease cancer. Investigating related risk factor measures may elucidate the biological burden of chronic pain. Objectives We hypothesized that severity would be positively composite. Methods Data from 12,982 participants in 6th Tromsø study were analyzed. Questionnaires included demographics, health behaviors, medical comorbidities, symptoms. The composite was comprised body mass...
Individuals with osteoarthritis (OA) show increased morbidity and mortality. Telomere length, a measure of cellular aging, predicts Telomeres shorten persisting biological psychosocial stress. Living chronic OA pain is stressful. Previous research exploring telomere length in people has produced inconsistent results. Considering severity may clarify the relationship between telomeres.We hypothesized that individuals high would have shorter telomeres than those no or low severity.One hundred...
Osteoarthritis (OA) is associated with inflammation, chronic pain, functional limitations, and psychosocial distress. High omega-3 (n-3) polyunsaturated fatty acids (PUFAs) are lower levels of inflammatory mediators, anti-nociception, adaptive cognitive/emotional functioning. omega-6 (n-6) PUFAs nociception, psychological While findings related to n-3 supplementation in knee OA mixed, consideration the n-6:n-3 ratio additional outcome measures may provide improved understanding potential...
In this article, we propose penalized spline (P-spline)-based methods for functional mixed effects models with varying coefficients. We decompose longitudinal outcomes as a sum of several terms: population mean function, covariates time-varying coefficients, subject-specific random effects, and residual measurement error processes. Using P-splines, nonparametric estimation the coefficient, curves, associated covariance function that represents between-subject variation variance errors which...
One useful approach for fitting linear models with scalar outcomes and functional predictors involves transforming the data to wavelet domain converting data-fitting problem a variable selection problem. Applying LASSO procedure in this situation has been shown be efficient powerful. In article, we explore two potential directions improvements method: techniques prescreening methods weighting LASSO-type penalty. We consider several strategies each of these which have never investigated,...
Summary Many techniques of functional data analysis require choosing a measure distance between functions, with the most common choice being distance. In this article we show that using weighted distance, judiciously chosen weight function, can improve performance various statistical methods for data, including k ‐medoids clustering, nonparametric classification, and permutation testing. Assuming quadratically penalized (e.g., spline) basis representation consider three nontrivial functions:...
Neuroimaging studies of cognitive and brain aging often yield massive datasets that create many analytic statistical challenges. In this paper, we discuss address several limitations in the existing work. 1) Linear models are used to model age effects on neuroimaging markers, which inadequate capturing potential nonlinear trends. 2) Marginal correlations network analysis, not efficient characterizing a complex network. 3) Due challenge high- dimensionality, only small subset regional markers...
In many clinical settings, a commonly encountered problem is to assess accuracy of screening test for early detection disease. these applications, predictive performance the interest. Variable selection may be useful in designing medical test. An example research study conducted design new by selecting variables from an existing screener with hierarchical structure among variables: there are several root questions followed their stem questions. The will only asked after subject has answered...
Multilevel functional data are collected in many biomedical studies. For example, a study of the effect Nimodipine on patients with subarachnoid hemorrhage (SAH), underwent multiple 4-hr treatment cycles. Within each cycle, subjects' vital signs were reported every 10 min. These have natural multilevel structure cycles nested within subjects and measurements Most literature nonparametric analysis such focuses conditional approaches using mixed effects models. However, parameters obtained...
We examine a generalized F-test of nonparametric function through penalized splines and linear mixed effects model representation. With representation splines, we imbed the test an unspecified into some fixed variance component in with nuisance components under null. The procedure can be used to or varying-coefficient clustered data, compare two spline functions, significance additive multiple components, row column effect two-way analysis model. Through spectral decomposition residual sum...
Palliative medicine is an interdisciplinary specialty focusing on improving quality of life (QOL) for patients with serious illness and their families. care programs are available or under development at over 80% large US hospitals (300+ beds). clinical trials present unique analytic challenges relative to evaluating the palliative treatment efficacy which improve patients’ diminishing QOL as disease progresses towards end (EOL). A feature that will experience decreasing during trial despite...
Precise modeling of disease progression in neurodegenerative disorders may enable early intervention before clinical manifestation a disease, which is crucial since at the premanifest stage expected to be more effective. Neuroimaging biomarkers are indicative underlying pathology and used predict future occurrence stage. As observed many pivotal studies, longitudinal measurements outcomes, such as motor or cognitive symptoms, often present nonlinear sigmoid shapes over time, where inflection...
Constructing classification rules for accurate diagnosis of a disorder is an important goal in medical practice. In many clinical applications, there no clinically significant anatomical or physiological deviation exists to identify the gold standard disease status inform development algorithms. Despite absence perfect class identifiers, are usually one more disease-informative auxiliary markers along with feature variables comprising known symptoms. Existing statistical learning approaches...