Journal of the American Medical Informatics Association (JAMIA)

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AI shows promise for clinical phenotyping

Researchers at Vanderbilt University Medical Center have demonstrated the potential for large language models like ChatGPT to help generate electronic health record phenotyping algorithms, a critical but time-consuming task in observational health research.

AI to doctors: Beat that! 

Artificial intelligence programs outperformed doctors at answering typical patient questions — suggesting they could be used to write first-draft responses and help speed doctors’ work.

AI aids efforts to cut nuisance alerts for health care teams: study

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.

Team uses COVID-19 to test automated acute disease profiling

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.

ChatGPT tested for clinical decision support

The problem with the problem list

Algorithms to infer missing problems and suggest that they be added to electronic health records improved problem list completeness, with benefits for clinical care, patient comprehension of health conditions and population health.

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