A Symptom-Based Natural Language Processing Surveillance Pipeline for Post-COVID-19 Patients

• Published in: Studies in health technology and informatics Vol. 310; p. 860
• Main Authors: Silverman, Greg M, Rajamani, Geetanjali, Ingraham, Nicholas E, Glover, James K, Sahoo, Himanshu S, Usher, Michael, Zhang, Rui, Ikramuddin, Farha, Melnik, Tanya E, Melton, Genevieve B, Tignanelli, Christopher J
• Format: Journal Article
• Language: English
• Published: Netherlands 25.01.2024
• Subjects: COVID-19 - epidemiology; Disease Progression; Health Care Costs; Humans; Natural Language Processing; SARS-CoV-2; PASC; disease surveillance; NLP

Post-acute sequelae of SARS CoV-2 (PASC) are a group of conditions in which patients previously infected with COVID-19 experience symptoms weeks/months post-infection. PASC has substantial societal burden, including increased healthcare costs and disabilities. This study presents a natural language...