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The Digital Face Of Airpower: Asymmetry, Artificial Intelligence And Intimate Combat In The Twenty-First Century United States Air Force, Jordan Bolster
The Digital Face Of Airpower: Asymmetry, Artificial Intelligence And Intimate Combat In The Twenty-First Century United States Air Force, Jordan Bolster
Masters Theses
Remotely piloted aircraft (RPA) operators have been at war for over twenty-years using unmanned aerial vehicles to kill combat enemies half-a-world away. Their emotional experiences provide an opportunity to examine intimacy in warfare which can be compared and contrasted with conventional pilots and traditional rifle-bearing ground troops. By comparing and contrasting specific emotions felt across various combat environments and technologies, it is possible to answer the question of whether or not RPA operators are legitimate warriors or legitimated assassins. The implementation of RPA operators in combat zones and the proliferation of unmanned technology on the battlefield open up new questions …
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 …