GHUCCTS

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MHRI-GHUCCTS Monthly Statistical Seminar: The Tableau Basics & How to Visualize COVID-19 Surveillance Data

Date Fri, May 21
Time 12: 00 PM - 1: 00 PM
Location Zoom


This month's MHRI-GHUCCTS Monthly Statistical Seminar Series features Christian Boxley, Senior Research Associate at MedStar Health National Center for Human Factors in Healthcare. Christian will discuss "The Tableau Basics: How to Visualize COVID-19 Surveillance Data".

ABSTRACT: Finding and communicating insights from large datasets is becoming increasingly important as our ability to access and generate data continues to grow. Tableau is a data visualization software tool that can be used to explore and understand your data. In this presentation, we will discuss the basics to getting started with Tableau, how I’ve used Tableau to visualize COVID-19 surveillance data, and some of Tableau’s limitations.


Headshot of Christian Boxley, smiling at the camera, wearing a suitChristian Boxley is a Senior Research Associate at the MedStar Health National Center for Human Factors in Healthcare. His research interests include using natural language processing techniques, data visualization, and predictive analytics to improve patient safety. While Christian primarily supports grant and contract funded research, the COVID-19 pandemic temporarily pushed him into a new role supporting MedStar Health operations. This work included providing analytics and situtational awareness dashboards for MedStar Health’s teleheath team, and more recently, he supported efforts in vaccination outreach. Christian received his bachelor’s degree in Biology of Global Health from Georgetown University, and he enjoys cooking new recipes and playing ultimate frisbee in his free time.

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This month's MHRI-GHUCCTS Monthly Statistical Seminar Series will be held Friday, October 15, 2021 online from 12 PM to 1 PM. This series features Dr. Paul Kolm, Associate Director in the Department of Biostatistics and Biomedical Informatics at MedStar Health Research Institute. Dr. Kolm will present on the topic Analytic Complexities of Observational Data: A Study of Modeling Atrial Fibrillation
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