Natural Language Processing for Improved Characterization of COVID-19 Symptoms: Observational Study of 350,000 Patients in a Large Integrated Health Care System

• Hauptverfasser: Deborah E Malden (VerfasserIn), Sara Y Tartof (VerfasserIn), Bradley K Ackerson (VerfasserIn), Vennis Hong (VerfasserIn), Jacek Skarbinski (VerfasserIn), Vincent Yau (VerfasserIn), Lei Qian (VerfasserIn), Heidi Fischer (VerfasserIn), Sally F Shaw (VerfasserIn), Susan Caparosa (VerfasserIn), Fagen Xie (VerfasserIn)
• Format: Buch
• Veröffentlicht: JMIR Publications, 2022-12-01T00:00:00Z.
• Schlagworte: article
• Online-Zugang: Connect to this object online.

BackgroundNatural language processing (NLP) of unstructured text from electronic medical records (EMR) can improve the characterization of COVID-19 signs and symptoms, but large-scale studies demonstrating the real-world application and validation of NLP for this purpose are limited. ObjectiveThe ai...