Digital Commons Network^™

Leveraging A Machine Learning Based Predictive Framework To Study Brain-Phenotype Relationships, Sage Hahn

Graduate College Dissertations and Theses

An immense collective effort has been put towards the development of methods forquantifying brain activity and structure. In parallel, a similar effort has focused on collecting experimental data, resulting in ever-growing data banks of complex human in vivo neuroimaging data. Machine learning, a broad set of powerful and effective tools for identifying multivariate relationships in high-dimensional problem spaces, has proven to be a promising approach toward better understanding the relationships between the brain and different phenotypes of interest. However, applied machine learning within a predictive framework for the study of neuroimaging data introduces several domain-specific problems and considerations, leaving the …

Developing Muscle Synergy Functions For Remote Gait Analysis, Nicole Marie Donahue

Graduate College Dissertations and Theses

Digital medicine promises to improve healthcare and enable its delivery to rural and underserved communities. A key component of digital medicine is accurate and robust remote patient monitoring. For example, remote monitoring of biomechanical measures of limb impairment during daily life could allow near real-time tracking of rehabilitation progress and personalization of rehabilitation paradigms in those recovering from orthopedic surgery. Wearable sensors have long been suggested as a means for quantifying muscle and joint loading, which can provide a direct measure of limb impairment. However, current approaches either do not provide these measures or require unwieldy wearable sensor arrays and/or …

Machine Learning For Species Classification Of The Invasive Centaurea Jacea Hybrid Complex, Sophie Linde

UVM Patrick Leahy Honors College Senior Theses

Abstract:

Proper taxonomic classification is important for biodiversity research and community ecology; however, it can be challenging for biologists to properly recognize and classify closely related species that visually appear very similar to one another. In the United States, the species Centaurea jacea ( C.jacea) and Centaurea nigra (C. nigra) and their hybrids are commonly found in New England, the Great Lakes and the Pacific Northwest. There is uncertainty regarding their identification and classification due to these species often interbreeding which results in hybrids that blur the species boundaries between Centaurea jacea and Centaurea nigra. …