At the National Heart Lung and Blood Institute (NHLBI), CIO Alastair Thomson says machine learning (ML) played a major role in COVID-related research. The National COVID Cohort Collaborative (NC3) clearly demonstrates the value of securely bringing together data in one place, where it can be analyzed by thousands of researchers. Through collaboration with various healthcare and cloud service providers, the NC3 and ML helped NIH identify potential participants for the RECOVER initiative.

“The utility of this really became clear when NIH launched the RECOVER initiative, which is dealing with post-acute COVID syndrome, or long COVID,” Thomson said at the annual AFCEA’s Health IT Summit last week. “They were able to use machine learning with that data to identify the key characteristics, what we call a phenotype, for long COVID.” …

At HHS OIG, ML capabilities are creating new efficiencies for its contracting grants analytics portal.

“This is a platform where we’re applying natural language processing techniques to pull out unstructured information from A133 grant reports,” said Keith Bocian, HHS OIG AI Lead. “Really looking at enhancing the transparency of the data in millions of pages of unstructured information so that our auditors, investigators, evaluators, can look at specific cases that trend in some of the large grant portfolios within HHS.” … Read the full article here.