Medicine and Health Sciences Commons^™

Influences Of Athletic Trainers' Return-To-Activity Assessments For Patients With An Ankle Sprain, Ryan S. Mccann, Cailee E. Welch Bacon, Ashley M. B. Suttmiller, Phillip A. Gribble, Julie M. Cavallario

Rehabilitation Sciences Faculty Publications

Context: Athletic trainers (ATs) inconsistently apply rehabilitation-oriented assessments (ROASTs) when deciding return-to-activity readiness for patients with an ankle sprain. Facilitators and barriers that are most influential to ATs' assessment selection remain unknown.

Objective: To examine facilitators of and barriers to ATs' selection of outcome assessments when determining return-to-activity readiness for patients with an ankle sprain.

Design: Cross-sectional study.

Setting: Online survey.

Patients or other participants: We sent an online survey to 10 000 clinically practicing ATs. The survey was accessed by 676 individuals, of whom 574 submitted responses (85% completion rate), and 541 respondents met the inclusion criteria.

Main outcome …

Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando

Community & Environmental Health Faculty Publications

Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …

Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Rapid early progression (REP) has been defined as increased nodular enhancement at the border of the resection cavity, the appearance of new lesions outside the resection cavity, or increased enhancement of the residual disease after surgery and before radiation. Patients with REP have worse survival compared to patients without REP (non-REP). Therefore, a reliable method for differentiating REP from non-REP is hypothesized to assist in personlized treatment planning. A potential approach is to use the radiomics and fractal texture features extracted from brain tumors to characterize morphological and physiological properties. We propose a random sampling-based ensemble classification model. The proposed …