Data Science Team

The Insight Discovery and Computational Modeling team is diverse team with backgrounds in statistics, computational biology, economics, manufacturing, and data science, and is member of the Cone Health Enterprise Analytics team. We specialize in applying advanced statistical, mathematical, and data science techniques to problems across the health system. Such topics covered include evaluation of methods, population cluster analysis, discrete/ agent based modeling, Bayesian inference, network analysis, time series analysis, and online prediction/ change-point detection.

Contact Us

Email The Data Science Team at Cone Health

Special Thanks

This website is largely inspired by the Epiforecasts team and their SARS-CoV-2 reporting. Additionally, their open sourcing of cutting edge modeling approaches was hugely beneficial.

The website was built using the distill framework (Allaire, Iannone, and Xie 2020) and R Markdown (Allaire et al. 2020).

Our Work in the Media

The Times News Over 900 new cases in a week reported in Alamance as state sets new COVID-19 records

Becker’s Health IT How Cone Health is using Facebook data to predict future COVID-19 cases

Rockingham Now (Greensboro News and Record) Cone Health Puts COVID-19 Data Analysis Online

Greensboro News and Record Cone Health could run out of hospital beds by Jan. 21, analysts warn. Community effort can change that, says physician.

Triad Business Journal Cone Health’s ‘sobering’ Covid-19 forecast shows system will surpass capacity this month

Winston Salem Journal Cone Health could run out of hospital beds by Jan. 21, analysts warn. Community effort can change that, says physician

Wilkes Journal-Patriot Area hospital capacity challenged

WFDD Cone Health’s New COVID-19 Website Includes Risk-Assessment Tool

WFMY News 2 Cone Health Data Science Team uses Facebook to help predict future COVID-19 cases, ‘The more COVID cases we have, the fewer non-COVID cases we can treat’ | Analysts predict Cone Health will exceed hospital capacity by January 21, ‘Cautious optimism’ | State sees another drop in hospitalizations, data scientist digs into trends

Allaire, JJ, Rich Iannone, and Yihui Xie. 2020. Distill: ’R Markdown’ Format for Scientific and Technical Writing. https://CRAN.R-project.org/package=distill.
Allaire, JJ, Yihui Xie, Jonathan McPherson, Javier Luraschi, Kevin Ushey, Aron Atkins, Hadley Wickham, Joe Cheng, Winston Chang, and Richard Iannone. 2020. Rmarkdown: Dynamic Documents for r. https://github.com/rstudio/rmarkdown.
Health, Cone. n.d. “The Network for Exceptional Care.” http://www.conehealth.com/.

References

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