Along with its toll on human lives across the planet, the COVID-19 pandemic has also produced untold amounts of data, in the form of medical records and news articles.
For Colorado State University Professor of Computer Science Indrakshi Ray, these mountains of data are an opportunity and a challenge to sift through the noise and help determine what’s true and what’s false.
Ray, a cybersecurity and database systems researcher, and a team of data science and medical experts, have received support from the National Science Foundation via an “jobs with computer science degree” proposal. They will spend the next year refining machine learning-based tools that help ensure the integrity of COVID-19 data and news across regions.
The $200,000 project has two parts: one looks at medical records, one at news content.
The first involves looking at COVID-19 patient records and determining whether any of the data contain anomalies, such as when malicious actors insert false records or delete real ones. To tackle this problem, Ray and the team will employ a machine learning toolset they have already applied to similar data quality-assessment problems in pre-COVID medical record databases.
For Colorado State University Professor of Computer Science Indrakshi Ray, these mountains of data are an opportunity and a challenge to sift through the noise and help determine what’s true and what’s false.
Ray, a cybersecurity and database systems researcher, and a team of data science and medical experts, have received support from the National Science Foundation via an “jobs with computer science degree” proposal. They will spend the next year refining machine learning-based tools that help ensure the integrity of COVID-19 data and news across regions.
The $200,000 project has two parts: one looks at medical records, one at news content.
The first involves looking at COVID-19 patient records and determining whether any of the data contain anomalies, such as when malicious actors insert false records or delete real ones. To tackle this problem, Ray and the team will employ a machine learning toolset they have already applied to similar data quality-assessment problems in pre-COVID medical record databases.
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