Medicine and Health 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 …

Optimization In Mri Experiment Design And Image Reconstruction, Mark Armstrong

Electronic Theses and Dissertations

Magnetic Resonance Imaging (MRI) is a non-invasive imaging modality with numerous applications due to its flexible contrast and high resolution. Recent improvements in computation power have enabled optimizations which were previously out of reach. This has led to improvements in image reconstruction and experiment design.

Compressed sensing (CS) allows for images to be reconstructed using less data than is normally required leading to faster image acquisitions. In this thesis, CS is applied to experiments tracking individual cells in time lapse MRI. The faster image acquisition with CS reduces blurring from cell motion, improving the Contrast-to-Noise ratio (CNR) of moving cells …