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Leveraging Context Patterns For Medical Entity Classification, Garrett Johnston
Leveraging Context Patterns For Medical Entity Classification, Garrett Johnston
Computer Science Senior Theses
The ability of patients to understand health-related text is important for optimal health outcomes. A system that can automatically annotate medical entities could help patients better understand health-related text. Such a system would also accelerate manual data annotation for this low-resource domain as well as assist in down- stream medical NLP tasks such as finding textual similarity, identifying conflicting medical advice, and aspect-based sentiment analysis. In this work, we investigate a state-of-the-art entity set expansion model, BootstrapNet, for the task of medical entity classification on a new dataset of medical advice text. We also propose EP SBERT, a simple model …
Destabilizing Terrorist Networks, John Keane
Destabilizing Terrorist Networks, John Keane
Dartmouth College Undergraduate Theses
Terrorism is a threat to global security and instills fear in the lives of people across the world. Over the past decades, billions in \$USD have been invested in counter-terrorism efforts. One approach to counter-terrorism is to destabilize terrorist organizations such that they are less effective at carrying out attacks. Previous work has investigated how to best proceed in this direction, such as which terrorists to target. Terrorist organizations have also been modeled as networks, where nodes can represent factions and/or terrorists. Research has been done to understand the network dynamics and link the structure of such networks to their …