Conditional random fields for clinical named entity recognition: A comparative study using Korean clinical texts

Computers in Biology and Medicine

Volumn 101, Issue , 2018, Pages 7-14

  Lee, Wangjin ^a   Kim, Kyungmo ^a   Lee, Eun Young ^b   Choi, Jinwook ^a,b  

^a Seoul National University   (South Korea)

^b Seoul National University College of Medicine   (South Korea)

Author keywords

Clinical named entity recognition; Conditional random field; Discharge summary; Medical history; String matching

Indexed keywords

DISEASES; HOSPITALS; IMAGE SEGMENTATION; RANDOM PROCESSES; SEMANTICS;

CONDITIONAL RANDOM FIELD; DISCHARGE SUMMARY; MEDICAL HISTORY; NAMED ENTITY RECOGNITION; STRING MATCHING;

NATURAL LANGUAGE PROCESSING SYSTEMS;

ACCURACY; ARTICLE; COMPARATIVE STUDY; HIDDEN MARKOV MODEL; HUMAN; MAJOR CLINICAL STUDY; NAMED ENTITY RECOGNITION; NATURAL LANGUAGE PROCESSING; PRIORITY JOURNAL; RHEUMATIC DISEASE; SEMANTICS; SOUTH KOREA; STATISTICAL ANALYSIS; SYMPTOM ASSESSMENT; DATA MINING; MEDICAL INFORMATICS; PROCEDURES;

DATA MINING; HUMANS; MEDICAL INFORMATICS; NATURAL LANGUAGE PROCESSING; REPUBLIC OF KOREA;

EID: 85050947903     PISSN: 00104825     EISSN: 18790534     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2018.07.019     Document Type: Article

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