Horvitz, an elected member of the National Academy of Engineering, is a pioneer in the applications of machine learning, AI and decision science.
The project seeks to reduce the time for clinical chart abstraction by 90% while maintaining human-level accuracy.
V-CARES will focus on detecting hallucinations, omissions and misaligned values in AI-generated responses on critical health topics.
VUMC was recognized thanks to the leadership of Vanderbilt’s Department of Biomedical Informatics and its new AI Discovery & Vigilance to Accelerate Innovation & Clinical Excellence.
AI has proven better than doctors at drafting responses to written questions from patients. A new study suggests even greater advantages in using AI to help patients write more effective messages to their care teams.
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.
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