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

Enhancing Clinical Concept Extraction with Contextual Embeddings

no code implementations • 22 Feb 2019 • Yuqi Si, Jingqi Wang, Hua Xu, Kirk Roberts

We explore a battery of embedding methods consisting of traditional word embeddings and contextual embeddings, and compare these on four concept extraction corpora: i2b2 2010, i2b2 2012, SemEval 2014, and SemEval 2015.

Clinical Concept Extraction Language Modelling +2

UTHealth at SemEval-2016 Task 12: an End-to-End System for Temporal Information Extraction from Clinical Notes

no code implementations • SEMEVAL 2016 • Hee-Jin Lee, Hua Xu, Jingqi Wang, Yaoyun Zhang, Sungrim Moon, Jun Xu, Yonghui Wu

Named Entity Recognition (NER) Temporal Information Extraction

UTH-CCB: The Participation of the SemEval 2015 Challenge -- Task 14

no code implementations • SEMEVAL 2015 • Jun Xu, Yaoyun Zhang, Jingqi Wang, Yonghui Wu, Min Jiang, Ergin Soysal, Hua Xu

Named Entity Recognition (NER) Slot Filling

UTH\_CCB: A report for SemEval 2014 -- Task 7 Analysis of Clinical Text

no code implementations • SEMEVAL 2014 • Yaoyun Zhang, Jingqi Wang, Buzhou Tang, Yonghui Wu, Min Jiang, Yukun Chen, Hua Xu