作者
Theresa A Koleck, Caitlin Dreisbach, Philip E Bourne, Suzanne Bakken
发表日期
2019/4
来源
Journal of the American Medical Informatics Association
卷号
26
期号
4
页码范围
364-379
出版商
Oxford University Press
简介
Objective
Natural language processing (NLP) of symptoms from electronic health records (EHRs) could contribute to the advancement of symptom science. We aim to synthesize the literature on the use of NLP to process or analyze symptom information documented in EHR free-text narratives.
Materials and Methods
Our search of 1964 records from PubMed and EMBASE was narrowed to 27 eligible articles. Data related to the purpose, free-text corpus, patients, symptoms, NLP methodology, evaluation metrics, and quality indicators were extracted for each study.
Results
Symptom-related information was presented as a primary outcome in 14 studies. EHR narratives represented various inpatient and outpatient clinical specialties, with general, cardiology, and mental health occurring most frequently. Studies encompassed a wide variety of symptoms …
学术搜索中的文章
TA Koleck, C Dreisbach, PE Bourne, S Bakken - Journal of the American Medical Informatics …, 2019