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Full-Text Articles in Physical Sciences and Mathematics
Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp
Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp
Theses and Dissertations--Epidemiology and Biostatistics
In this series of studies, we examined the potential of a variety of blood-based plasma biomarkers for the identification of Alzheimer's disease (AD) progression and cognitive decline. With the end goal of studying these biomarkers via mixture modeling, we began with a literature review of the methodology. An examination of the biomarkers with demographics and other health factors found evidence of minimal risk of confounding along the causal pathway from biomarkers to cognitive performance. Further study examined the usefulness of linear combinations of biomarkers, achieved via partial least squares (PLS) analysis, as predictors of various cognitive assessment scores and clinical …
Statistical Intervals For Neural Network And Its Relationship With Generalized Linear Model, Sheng Yuan
Statistical Intervals For Neural Network And Its Relationship With Generalized Linear Model, Sheng Yuan
Theses and Dissertations--Statistics
Neural networks have experienced widespread adoption and have become integral in cutting-edge domains like computer vision, natural language processing, and various contemporary fields. However, addressing the statistical aspects of neural networks has been a persistent challenge, with limited satisfactory results. In my research, I focused on exploring statistical intervals applied to neural networks, specifically confidence intervals and tolerance intervals. I employed variance estimation methods, such as direct estimation and resampling, to assess neural networks and their performance under outlier scenarios. Remarkably, when outliers were present, the resampling method with infinitesimal jackknife estimation yielded confidence intervals that closely aligned with nominal …