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Articles 1 - 2 of 2
Full-Text Articles in Other Medical Sciences
A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb
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 …
Development Of A Low-Dose Radiation Therapy Device For Acute Respritory Distress Syndrome, Thomas Heath Davis
Development Of A Low-Dose Radiation Therapy Device For Acute Respritory Distress Syndrome, Thomas Heath Davis
Masters Theses
This research focuses on the development of a low dose radiotherapy (LD-RT) device for treatment of acute respiratory distress syndrome (ARDS), a respiratory illness that affects millions of people a year. The use of orthovoltage (200 – 500 keV) X-ray energy provides many advantages over traditional radiotherapy delivery with linear accelerators, such as low cost and greater accessibility. In addition, X-ray tubes have been shown throughout history to provide good treatment outcomes for pneumonia, and research has shown LD-RT to be just as effective with ARDS. This proposal summarizes my efforts in determining the dosimetric properties of a LD-RT system …