Colorado State U to deploy machine-learning tool that can detect falsified COVID-19 medical records

Listen
Text
  • Small
  • Medium
  • Large

The National Science Foundation awarded nearly $200,000 to Colorado State University and University of Colorado researchers to build machine-learning tools that can verify the integrity of COVID-19 patient medical records.

The Fort Collins-based university will team up with Aurora-based University of Colorado Anschutz Medical Campus researchers to analyze COVID-19 patient records to determine whether any data contains anomalies, such as when malicious individuals add false records or delete authentic records.

Led by Indrakshi Ray, computer science professor at Colorado State University, the research team will use a machine learning toolset that the university already uses to assess similar data quality issues in pre-COVID-19 medical record databases, according to the news release. The tool is able to automate anomaly detection by arranging suspicious medical records into clusters that are easier to sift through and validate than thousands of records in one database.

The second part of the research will apply the machine learning tools to examine large volumes of news articles and digital content to identify which have been tampered with or changed.

 

Copyright © 2021 Becker's Healthcare. All Rights Reserved. Privacy Policy. Cookie Policy. Linking and Reprinting Policy.

 

Featured Whitepapers

Featured Webinars