electronic health records (EHRs)

A new study from Vanderbilt University Medical Center demonstrates the promise of artificial intelligence to help refine and target the myriad computerized alerts intended to assist doctors and other team members in day-to-day clinical decision-making.

Vanderbilt's Ashley Spann, MD, MSACI, is the inaugural recipient of the Harold Amos Medical Faculty Development Program Hepatology Award from the American Association for the Study of Liver Diseases.

In a new study across three major U.S. health care systems, researchers developed and tested algorithms to predict who will develop bipolar disorder.

The STAR Clinical Research Network, based at Vanderbilt University Medical Center (VUMC), has added two new partners — Essentia Health, a Minnesota-based rural health care system, and Stanford University School of Medicine, one of the country’s leading academic medical centers.

An automated solution for creating phenotyping algorithms, PheNorm, worked well to identify symptomatic COVID-19 cases in electronic health records, suggesting that automation could speed high-throughput phenotyping of acute disease.

A Vanderbilt study found that automated suicide risk prediction models operating on electronic health records could help clinical teams efficiently identify patients for face-to-face suicide risk screening and prevention.

Vanderbilt's Bryan Shepherd, PhDhas received a MERIT Award, or Method to Extend Research in Time Award, from the National Institute of Allergy and Infectious Diseases.