基于语义对齐的临床量表信息提取方法及其临床试验队列识别的应用研究  

Extracting Clinical Scale Information and Identifying Trial Cohorts with Semantic Alignment

作　　者：杨林[1] 黄晓硕 王嘉阳 李姣[1] Yang Lin;Huang Xiaoshuo;Wang Jiayang;Li Jiao(Institute of Medical Infbrmation/Medical Library,Chinese Academy of Medical Science&Peking Union Medical College,Beijing 100020,China)

机构地区：[1]中国医学科学院/北京协和医学院医学信息研究所/图书馆,北京100020

出　　处：《数据分析与知识发现》2020年第12期33-44,共12页Data Analysis and Knowledge Discovery

基　　金：中国医学科学院中央级公益性科研院所基本科研业务费项目“医学人工智能技术与人机交互关键问题研究”(项目编号:2018PT33024)、“真实世界临床数据感知与智能处理技术研究”(项目编号:2017PT63010)和中国医学科学院医学与健康科技创新工程“医学人工智能算法评价标准库构建”(项目编号:2018-I2M-AI-016)的研究成果之一。

摘　　要：【目的】面向真实世界数据驱动的临床研究需求,提出一种基于语义对齐的临床量表信息提取方法,辅助识别潜在受试人群。【方法】选取卒中量表NIHSS,分析量表信息在临床试验和真实世界电子病历中的特征,构建基于语义对齐的量表信息提取方法,应用临床试验数据集(ClinicalTrials.gov)和开放电子病历数据集MIMIC-Ⅲ开展实验验证。【结果】从患者出院小结中抽取NIHSS总评分、检查项评分的F1值分别为0.9535和0.9267;围绕两项匹配NIHSS纳排标准的测试任务,可以有效地识别出潜在受试人群。【局限】缺乏在其他量表上的可行性研究,以及在真实临床试验环境中的有效性和可靠性验证。【结论】本方法可以有效地解决临床量表信息在临床研究与电子病历数据的语义一致性问题。[Objective] This study develops a method to extract clinical scale information based on semantic alignment, aiming to identify the potential cohort and improve the data-driven clinical research. [Methods] First,we analyzed the features of National Institutes of Health Stroke Scale(NIHSS) with clinical trials and real-world electronic medical records. Then, we proposed an extraction method for clinical scale information based on semantic alignment. Finally, we examined our model with data from ClinicalTrials. gov and open electronic medical record dataset MIMIC-III. [Results] The F1 values of the NIHSS total score and item scores of the extracted contents were 0.953 5 and 0.926 7. We identified patients who met NIHSS criteria effectively.[Limitations] More research is needed to examine this method with other clinical scales and real-world trial recuriment scenario. [Conclusions] The proposed method could effectively address the issue of semantic consistency facing clinical scale information.

关 键 词：语义对齐 临床量表 临床试验 纳排标准 队列识别 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]