UCLA researchers have developed an AI system that turns fragmented electronic health records (EHR) normally in tables into readable narratives, allowing artificial intelligence to make sense of complex patient histories and use these narratives to perform clinical decision support with high accuracy. The Multimodal Embedding Model for EHR (MEME) transforms tabular health data into “pseudonotes” that mirror clinical documentation, allowing AI models designed for text to analyze patient information more effectively.
AI model converts hospital records into text for better emergency care decisions
Tech News
-
Highlights
Free Dark Web Monitoring Stamps the $17 Million Credentials Markets
-
Highlights
Smart buildings: What happens to our free will when tech makes choices for us?
-
Apps
Screenshots have generated new forms of storytelling, from Twitter fan fiction to desktop film
-
Highlights
Darknet markets generate millions in revenue selling stolen personal data, supply chain study finds
-
Security
Privacy violations undermine the trustworthiness of the Tim Hortons brand
-
Featured Headlines
Why Tesla’s Autopilot crashes spurred the feds to investigate driver-assist technologies – and what that means for the future of self-driving cars