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.
In a new study across three major U.S. health care systems, researchers developed and tested algorithms to predict who will develop bipolar disorder.
Vanderbilt Health adult ambulatory clinics began providing self check-in for appointments in late summer 2023, and the process has proven beneficial to both patients and staff.
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 team has received funding to pursue research projects deploying artificial intelligence (AI) and machine learning (ML) algorithms to enhance diagnostic decision-making in health care.
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.
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