title: Automatic de-identification of electronic medical records using token-level and character-level conditional random fields.
abstract: De-identification, identifying and removing all protected health information (PHI) present in clinical data including electronic medical records (EMRs), is a critical step in making clinical data publicly available. The 2014 i2b2 (Center of Informatics for Integrating Biology and Bedside) clinical natural language processing (NLP) challenge sets up a track for de-identification (track 1). In this study, we propose a hybrid system based on both machine learning and rule approaches for the de-identification track. In our system, PHI instances are first identified by two (token-level and character-level) conditional random fields (CRFs) and a rule-based classifier, and then are merged by some rules. Experiments conducted on the i2b2 corpus show that our system submitted for the challenge achieves the highest micro F-scores of 94.64%, 91.24% and 91.63% under the "token", "strict" and "relaxed" criteria respectively, which is among top-ranked systems of the 2014 i2b2 challenge. After integrating some refined localization dictionaries, our system is further improved with F-scores of 94.83%, 91.57% and 91.95% under the "token", "strict" and "relaxed" criteria respectively.
authors.affiliation: Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China. Electronic address: liuzengjian.hit@gmail.com.
authors.forename: Zengjian
authors.initials: Z
authors.lastname: Liu
authors.affiliation: Department of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou 510120, China. Electronic address: tjcyx1995@163.com.
authors.forename: Yangxin
authors.initials: Y
authors.lastname: Chen
authors.affiliation: Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China. Electronic address: tangbuzhou@gmail.com.
authors.forename: Buzhou
authors.initials: B
authors.lastname: Tang
authors.affiliation: Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China. Electronic address: wangxl@insun.hit.edu.cn.
authors.forename: Xiaolong
authors.initials: X
authors.lastname: Wang
authors.affiliation: Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China. Electronic address: qingcai.chen@gmail.com.
authors.forename: Qingcai
authors.initials: Q
authors.lastname: Chen
authors.affiliation: Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China. Electronic address: haodili.hit@gmail.com.
authors.forename: Haodi
authors.initials: H
authors.lastname: Li
authors.affiliation: Department of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou 510120, China. Electronic address: dr_wjf@hotmail.com.
authors.forename: Jingfeng
authors.initials: J
authors.lastname: Wang
authors.affiliation: The Sixth People's Hospital of Shenzhen, Shenzhen 518052, China. Electronic address: qiwendeng@hotmail.com.
authors.forename: Qiwen
authors.initials: Q
authors.lastname: Deng
authors.affiliation: The Sixth People's Hospital of Shenzhen, Shenzhen 518052, China. Electronic address: 13809883596@163.com.
authors.forename: Suisong
authors.initials: S
authors.lastname: Zhu
mesh_terms: D002681:China; D015331:Cohort Studies; D016494:Computer Security; D003219:Confidentiality; D003627:Data Interpretation, Statistical; D057225:Data Mining / Q000379:methods*; D057286:Electronic Health Records / Q000458:organization & administration*; D033262:Narration; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D018875:Vocabulary, Controlled
keywords: De-identification; Electronic medical records; Hybrid method; Natural language processing; Protected health information; i2b2