http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Andrés Orozco-Duque (검색결과 1 건)
- 무료
- 기관 내 무료
- 유료
-
Named Entity Recognition in Electronic Health Records: A Methodological Review
María C. Durango,Ever A. Torres-Silva,Andrés Orozco-Duque 대한의료정보학회 2023 Healthcare Informatics Research Vol.29 No.4
Objectives: A substantial portion of the data contained in Electronic Health Records (EHR) is unstructured, often appearingas free text. This format restricts its potential utility in clinical decision-making. Named entity recognition (NER) methodsaddress the challenge of extracting pertinent information from unstructured text. The aim of this study was to outline thecurrent NER methods and trace their evolution from 2011 to 2022. Methods: We conducted a methodological literature reviewof NER methods, with a focus on distinguishing the classification models, the types of tagging systems, and the languagesemployed in various corpora. Results: Several methods have been documented for automatically extracting relevant informationfrom EHRs using natural language processing techniques such as NER and relation extraction (RE). These methodscan automatically extract concepts, events, attributes, and other data, as well as the relationships between them. Most NERstudies conducted thus far have utilized corpora in English or Chinese. Additionally, the bidirectional encoder representationfrom transformers using the BIO tagging system architecture is the most frequently reported classification scheme. Wediscovered a limited number of papers on the implementation of NER or RE tasks in EHRs within a specific clinical domain. Conclusions: EHRs play a pivotal role in gathering clinical information and could serve as the primary source for automatedclinical decision support systems. However, the creation of new corpora from EHRs in specific clinical domains is essential tofacilitate the swift development of NER and RE models applied to EHRs for use in clinical practice.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
