COVID-19 SignSym: a fast adaptation of a general clinical NLP tool to identify and normalize COVID-19 signs and symptoms to OMOP common data model

no code implementations • 13 Jul 2020 • Jingqi Wang, Noor Abu-el-rub, Josh Gray, Huy Anh Pham, Yujia Zhou, Frank Manion, Mei Liu, Xing Song, Hua Xu, Masoud Rouhizadeh, Yaoyun Zhang

To this end, this study aims at adapting the existing CLAMP natural language processing tool to quickly build COVID-19 SignSym, which can extract COVID-19 signs/symptoms and their 8 attributes (body location, severity, temporal expression, subject, condition, uncertainty, negation, and course) from clinical text.

Negation

Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance

no code implementations • 13 Dec 2015 • Mauricio Santillana, Andre Nguyen, Tamara Louie, Anna Zink, Josh Gray, Iyue Sung, John S. Brownstein

Accurate real-time monitoring systems of influenza outbreaks help public health officials make informed decisions that may help save lives.

BIG-bench Machine Learning