Computer Engineering Commons^™

Machine Learning Approaches For Fracture Risk Assessment: A Comparative Analysis Of Genomic And Phenotypic Data In 5130 Older Men, Qing Wu, Fatma Nasoz, Jongyun Jung, Bibek Bhattarai, Mira V. Han

Public Health Faculty Publications

The study aims were to develop fracture prediction models by using machine learning approaches and genomic data, as well as to identify the best modeling approach for fracture prediction. The genomic data of Osteoporotic Fractures in Men, cohort Study (n = 5130), were analyzed. After a comprehensive genotype imputation, genetic risk score (GRS) was calculated from 1103 associated Single Nucleotide Polymorphisms for each participant. Data were normalized and split into a training set (80%) and a validation set (20%) for analysis. Random forest, gradient boosting, neural network, and logistic regression were used to develop prediction models for major osteoporotic fractures …

Forget-Me-Not, Daniel Barber-Cironi, Shawn Nicholson, Jake Kruse, Nicole Dent

Williams Honors College, Honors Research Projects

The purpose of Forget-Me-Not is to provide another level of care and comfort to those suffering from mild dementia, as well as provide further assistance for a friend, family member, or caretaker who may look after them. Research shows that timely reminders and persistent information can greatly improve the quality of life for those afflicted with mild dementia (Mokhtari et al.). Forget-Me-Not’s persistent display and wearable smart-bracelet offer a customizable and well connected system to provide these reminders. For the caretaker, a mobile application is provided in order to maintain the display and notify them of emergencies or critical events …

Embedded System Design For Real-Time Monitoring Of Solitary Embedded System Design For Real-Time Monitoring Of Solitary, Robert Philip O'Brien

USF Tampa Graduate Theses and Dissertations

Alzheimer's disease and other forms of dementia cause cognitive disabilities in the afflicted person. As a result, the person with dementia often requires assistance from a primary caregiver. However, while the caregiver is away from the home they are unaware of the person's status and may not be able to find out without returning to the home due to dementia's effects on cognition.

In this thesis work, a system of embedded devices is presented which tracks a solitary dementia patient in the home in real-time. The system is composed of three main hardware components. Multiple passive and active sensors are …