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RF sensing and processing methods for noninvasive health monitoring
(University of Missouri--Columbia, 2021)
Vulnerable populations include groups of people with a higher risk of poor health as a result of the limitations due to illness or disability. The health issues of vulnerable populations include three categories: physical, psychological, and social...
Personalized functional health and fall risk prediction using electronic health records and in-home sensor data
(University of Missouri--Columbia, 2021)
obtained from TigerPlace, a senior living facility at Columbia, MO. The de-identification of this data was done using custom automated algorithms. The de-identified EHR data was used in several studies described in this dissertation. We then developed...
Explainable data fusion
(University of Missouri--Columbia, 2021)
The recent resurgence of Artificial Intelligence (AI), specifically in the context of applications like healthcare, security and defense, IoT, and other areas that have a big impact on human life, has led to a demand for eXplainable AI (XAI...
Temporal decision making using unsupervised learning
(University of Missouri--Columbia, 2021)
are detected, and that new clusters are automatically formed as incoming data dictate. In this dissertation, we develop a streaming clustering algorithm, MU Streaming Clustering (MUSC), that is based on coupling a Gaussian mixture model (GMM) with possibilistic...