Description
This dissertation investigates the classification of systemic lupus erythematosus (SLE) in the presence of non-SLE alternatives, while developing novel curve classification methodologies with wide ranging applications. Functional data representations of plasma thermogram measurements and the corresponding derivative curves provide predictors yet to be investigated for SLE identification.
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Contributors
- Buscaglia, Robert, Ph.D (Author)
- Kamarianakis, Yiannis (Thesis advisor)
- Armbruster, Dieter (Committee member)
- Lanchier, Nicholas (Committee member)
- McCulloch, Robert (Committee member)
- Reiser, Mark R. (Committee member)
- Arizona State University (Publisher)
Date Created
- 2018
Subjects
- Statistics
- biostatistics
- Applied Mathematics
- Classification
- Ensemble Learning
- Functional Data Analysis
- Lupus
- supervised learning
- Supervised learning (Machine learning)
- Functional analysis
- Multivariate analysis
- Derivatives (Mathematics)
- Systemic lupus erythematosus
- Blood plasma
- Thermal Analysis
- Diagnosis--Data processing.
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Note
- Partial requirement for: Ph.D., Arizona State University, 2018Note typethesis
- Includes bibliographical references (pages 180-187)Note typebibliography
- Field of study: Applied mathematics
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Statement of Responsibility
by Robert Buscaglia