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Full-Text Articles in Medicine and Health Sciences
A New Spatially-Resolved Method To Sample Biofilms From Drinking Water Fountains, Yi Liu
A New Spatially-Resolved Method To Sample Biofilms From Drinking Water Fountains, Yi Liu
McKelvey School of Engineering Theses & Dissertations
A drinking fountain, also called a water fountain, is a facility designed to provide drinking water in public space. It consists of a basin and a spout. The users need to bend down to the stream to collect or drink water. The history of water fountains can be traced back to ancient Rome. Even before potable water was provided to individual homes, water for drinking was already made available to citizens through access to public fountains. Nowadays, drinking water fountains usually exist in public places, like schools, hospitals, and libraries. Many jurisdictions in the United States require drinking fountains to …
Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim
Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim
McKelvey School of Engineering Theses & Dissertations
Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross-sectional nature of training and prediction processes. Finding temporal patterns in EHR is especially …
Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim
Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim
McKelvey School of Engineering Theses & Dissertations
Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross- sectional nature of training and prediction processes. Finding temporal patterns in EHR is …