基于电子病历数据的临床表型提取及其应用进展

Development of Clinical Phenotype Extraction and Application Based on Electronic Medical Records(EMR) Data

在介绍临床表型提取技术的基础上,利用临床决策支持技术、自然语言处理技术和机器学习方法,就从糖尿病相关电子病历中提取临床表型等方面进行系统综述,表明深度学习方法可以更高效准确地从电子病历数据中提取出临床表型,帮助临床研究人员更好地进行临床试验,提高医疗护理水平。

Based on the introduction to the clinical phenotype extraction technique, the paper conducts systematic review on the extraction of clinical phenotype from Electronic Medical Records（ EMR） of diabetes by taking advantages of the clinical decision support technique, natural language processing technique and machine learning method, and indicates that the deep learning method can be used to extract clinical phenotype from the EMR data more effectively and accurately, help clinical researchers better conduct clinical tests,and improve the medical care level.