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Full-Text Articles in Medicine and Health Sciences
Identifying Locations Of Drug Overdose In Las Vegas To Implement The Cardiff Violence Prevention Model, John Girard, Shikha Pandey, Zack Bunn, Chris Papesh, Jacquelyn Cheun Phd, Ying Zhang
Identifying Locations Of Drug Overdose In Las Vegas To Implement The Cardiff Violence Prevention Model, John Girard, Shikha Pandey, Zack Bunn, Chris Papesh, Jacquelyn Cheun Phd, Ying Zhang
SMU Data Science Review
This paper will provide an innovative approach to drug overdose prevention programs. Using data from Las Vegas emergency departments, this paper will analyze geospatial trends of drug overdoses. Leveraging the Cardiff Violence Prevention Model, the information is shared with local law enforcement agencies and decision makers to empower them to make evidence-based strategies. This paper highlights the efficacy of a data-driven model in addressing public health issues and underscoring its ability for even broader implementation in urban settings. Findings will suggest significant implications for policymaking, crime prevention, and public health initiatives, demonstrating a step towards a safer Las Vegas.
A Novel Methodology To Identify The Primary Topics Contained Within The Covid-19 Research Corpus, Allen Crane, Brock Freidrich, William Fehlman, Igor Frolow, Daniel W. Engels
A Novel Methodology To Identify The Primary Topics Contained Within The Covid-19 Research Corpus, Allen Crane, Brock Freidrich, William Fehlman, Igor Frolow, Daniel W. Engels
SMU Data Science Review
In this paper, we present a novel framework and system for the identification of primary research topics from within a corpus of related publications, the classification of individual publications according to these topics, and the results of the application of our framework and system to the COVID-19 Open Research Dataset (CORD-19). CORD-19 is a corpus of published peer reviewed and pre-peer reviewed articles related to the coronavirus that causes COVID-19. Using machine learning techniques, such as Non-negative Matrix Factorization for Natural Language Processing and a Bayesian classifier, we developed a novel framework and system that automatically extracts sparse and meaningful …