Physical Sciences and Mathematics | Open Access Articles

Predictors Of Covid-19 Vaccination Rate In Usa: A Machine Learning Approach, Syed M. I. Osman, Ahmed Sabit

WCBT Faculty Publications

In this study, we examine state-level features and policies that are most important in achieving a threshold level vaccination rate to curve the effects of the COVID-19 pandemic. We employ CHAID, a decision tree algorithm, on three different model specifications to answer this question based on a dataset that includes all the states in the United States. Workplace travel emerges as the most important predictor; however, the governors’ political affiliation (PA) replaces it in a more conservative feature set that includes economic features and the growth rate of COVID-19 cases. We also employ several alternative algorithms as a robustness check. …

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Volitional Control Of Lower-Limb Prosthesis With Vision-Assisted Environmental Awareness, S M Shafiul Hasan

FIU Electronic Theses and Dissertations

Early and reliable prediction of user’s intention to change locomotion mode or speed is critical for a smooth and natural lower limb prosthesis. Meanwhile, incorporation of explicit environmental feedback can facilitate context aware intelligent prosthesis which allows seamless operation in a variety of gait demands. This dissertation introduces environmental awareness through computer vision and enables early and accurate prediction of intention to start, stop or change speeds while walking. Electromyography (EMG), Electroencephalography (EEG), Inertial Measurement Unit (IMU), and Ground Reaction Force (GRF) sensors were used to predict intention to start, stop or increase walking speed. Furthermore, it was investigated whether …

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A Keyword-Enhanced Approach To Handle Class Imbalance In Clinical Text Classification, Andrew E. Blanchard, Shang Gao, Hong Jun Yoon, J. Blair Christian, Eric B. Durbin, Xiao Cheng Wu, Antoinette Stroup, Jennifer Doherty, Stephen M. Schwartz, Charles Wiggins, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi

School of Public Health Faculty Publications

Recent applications ofdeep learning have shown promising results for classifying unstructured text in the healthcare domain. However, the reliability of models in production settings has been hindered by imbalanced data sets in which a small subset of the classes dominate. In the absence of adequate training data, rare classes necessitate additional model constraints for robust performance. Here, we present a strategy for incorporating short sequences of text (i.e. keywords) into training to boost model accuracy on rare classes. In our approach, we assemble a set of keywords, including short phrases, associated with each class. The keywords are then used as …

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Full-Text Articles in Physical Sciences and Mathematics

Predictors Of Covid-19 Vaccination Rate In Usa: A Machine Learning Approach, Syed M. I. Osman, Ahmed Sabit

WCBT Faculty Publications

Volitional Control Of Lower-Limb Prosthesis With Vision-Assisted Environmental Awareness, S M Shafiul Hasan

FIU Electronic Theses and Dissertations

School of Public Health Faculty Publications