CDS Against COVID-19

Image from Center for Data Science website, design by Ashley C. McDonald

In conjunction with the wider NYU community, we have developed and assembled a number of resources and initiatives working to minimize the negative impact of COVID-19. We have created a page on our website titled NYU Mobilizes Against COVID-19, which houses information on these projects. Here’s a little bit on what we’ve been working on…

• We have developed a skill matching program where we connect those seeking data science expertise with appropriate talent and support from our researchers, students, and faculty. For example, the NYU Marron Institute is developing statistical models and other means of analysis to explain disparities in case and death rates in the U.S., specifically at the Metropolitan level. For this, they sought assistance in building a website that would display metro area data with maps and visualizations on a daily basis. One of our students is currently contributing their skills to aid in completion of this essential component of their project.
• We’ve partnered with the NYU Grossman School of Medicine on a deep learning project which focuses on modeling and prediction of X-rays of patients suffering from COVID-19. Their goal is to use deep learning to predict the risk of deterioration based on the appearance of chest X-rays that are routinely collected in the emergency department. The School of Medicine has also collaborated with our professor Rajesh Ranganath’s lab in building models to predict the risk of adverse events for emergency department COVID-19 patients based on electronic health records.
• Our PhD student Zhouhan Chen has created a website called Misinformation Tracer, a cross-platform analysis system focused on the spread of misinformation. The tool is currently working to collect and analyze URLs related to the COVID-19 pandemic. Ultimately, the tracer takes a list of URLs as input, and automatically collects posts/tweets containing those URLs from four social media platforms: Twitter, Facebook, Instagram, and Reddit. Following that collection of data, a python script loads it, calculates summary statistics, and generates a Jupyter Notebook in HTML format, which is subsequently published on their website.

Other related initiatives previously covered by our blog include the Neural Covidex and Breathe for Science projects.

To learn more about our efforts against coronavirus, please visit our NYU Mobilizes Against COVID-19 page.

By Ashley C. McDonald