Other Medical Sciences Commons^™

A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb

Masters Theses

One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …

Support Their Sleep: Enhancing Nurses' Knowledge And Implementation Of Non-Pharmacological Sleep Protocols To Improve Patient Rest, Recovery, And Reduce Cognitive Impairment., David C. Barry

Master's Theses and Capstones

Background: Sleep and rest play an influential role in promoting recovery and healing in humans. Hospitalized patients are at risk for altered sleep from hospitalization, illness, and stimulation from a hospital environment. Non-pharmacologic interventions preformed by nurses can help to improve sleep and sleep environment for patients.

Local problem: There was no protocol or available information regarding patient sleep promotion for nurses to references when caring for patients.

Methods: Nurses in the microsystem (n=8) were administered a pre/post questionnaire containing Likert scales and a short quiz containing knowledge-based questions. Questionnaires were distributed to nurses prior to and after …