Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition

BackgroundPrevious state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text “feature engineering” and conventional machine learning algorithms such as conditional random fields and support vector machines. However, developing good features is inherently heavily time-consuming. Conversely, more modern machine learning approaches such as recurrent neural networks (RNNs) have proved capable of automatically learning effective features from either random assignments or automated word “embeddings”.Objectives(i) To create a highly accurate DNR and CCE system that avoids conventional, time-consuming feature engineering. (ii) To create richer, more specialized word embeddings by using health domain datasets such as MIMIC-III. (iii) To evaluate our systems over three contemporary datasets.MethodsTwo deep learning methods, namely the Bidirectional LSTM and the Bidirectional LSTM-CRF, are evaluated. A CRF model is set as the baseline to compare the deep learning systems to a traditional machine learning approach. The same features are used for all the models.ResultsWe have obtained the best results with the Bidirectional LSTM-CRF model, which has outperformed all previously proposed systems. The specialized embeddings have helped to cover unusual words in DrugBank and MedLine, but not in the i2b2/VA dataset.ConclusionsWe present a state-of-the-art system for DNR and CCE. Automated word embeddings has allowed us to avoid costly feature engineering and achieve higher accuracy. Nevertheless, the embeddings need to be retrained over datasets that are adequate for the domain, in order to adequately cover the domain-specific vocabulary.     

学术论文作者机构规范文档构建

以中国生物医学文献数据库为基础,面向基于学术论文开展机构检索、分析与评价相关知识服务需要,对学术论文作者机构名称规范目标与内容、体系结构与组织方式以及构建过程与实现策略进行研究、实践总结。     

新冠疫情形势下食品药品检验机构的担当与思考

新型冠状病毒肺炎疫情期间,各地食品药品检验机构积极发挥专业特长和检验优势,采取特事特办、抽检结合、组团帮扶等多项举措,为企业提供应急检验服务,为食品药品监管部门提供强有力技术支撑,彰显了食品药品检验机构的责任与担当。本文列举了部分食品药品检验机构开展的疫情防控保障工作,论述了食品药品检验工作的现实意义和社会价值,并对后疫情时期的检验检测工作模式作了思考。     

论中医“症状性病名”的合理性

症状性病名是病名演变过程中的必然阶段,也是以症状为纲目编撰医籍的需要,虽然症状性病名因症病概念混淆饱受诟病,但基于症状性病名仍有其存在的合理性和必要性,当前临床的关键问题是如何在继续继承及发展症状性病名同时,综合应用中医诊断基本要素、西医病名诊断与客观检查指标,弥补症状性病名应用短板。     

论中医“症”描述的准确性与规范化

“症”是中医诊断体系中最具体的要素,症状信息规范化其关键在于明确“症”的认识和理解,文章系统分析中医“症”的内涵,分析目前“症”规范化中存在的主要问题,如缺乏统一标准、各家之言迥异、中西医“症”的混杂等,这些一定程度上阻碍了中医临床与科研,不利于中医学术的交流及中医诊断学的现代化研究。因此提出从明确症名定义、统一规范症名、拆分复合症名、区分症状轻重、避免诊断性症名、纳入客观指征等几个方面对中医“症”的描述进行规范,通过建立系统标准体系,进行“症”的量化分级,规范信息采集过程,借助微观指标辨证等开展中医“症”的规范化研究。     

从瘟疫病名研究进展探讨疫病文献筛选思路

[目的] 通过梳理瘟疫病名的研究进展,获取古医籍中疫病文献的筛选思路。 [方法] 首先明确瘟疫的定义,阐述其主要分类方式,对温病、伤寒等相关名词进行考辨。而后将疫病文献分为笼统的瘟疫和具体的病种2大类,列举今人对相关术语的研究进展。[结果] 瘟疫指具有传染或流行特征而且伤亡较严重的一类疾病。按寒热性质分为温疫、寒疫和杂疫,温疫又可分为温热疫、湿热疫和暑热疫。瘟疫和温病的概念是交叉的,其交集部分为温疫。瘟疫本属广义伤寒,后逐渐脱离伤寒独立,其与传染病的关系仍存在争议。从文献中梳理出概述性瘟疫名称3种:(1)“疒”部的瘟疫全称;(2)以时令与流行命名的术语;(3)其他。制作“传染病中西医病名对照表”,涵盖传染病6类53种,包括病毒性传染病、立克次体病、细菌性传染病、螺旋体病、原虫病和蠕虫病。[结论] 本研究厘清了瘟疫的概念,找到了打开疫病文献宝库的钥匙,在相关研究中具有“破局”的效果。     

白涩症源流浅析

本文通过对历史相关古籍文献的整理研究,梳理白涩症发展沿革,探讨历代医家对其病因病机及治疗方法的认识,以期为白涩症的研究提供理论基础,并为临床治疗开拓思路。中医对白涩症的相关记载,最早可追溯至晋代《针灸甲乙经》中有关目涩的论述,其对于自觉眼部干涩不适的症状有了初步的认识。“白涩症”之名首见于《证治准绳》,后沿用至今。其基本病因病机主要归责于津液亏少,眼目不得濡养,外感邪气、脏腑内伤、情志失常、饮食劳倦等因素均可致病,内治法治疗主要分为祛邪、泻实、补虚三个方面,外治法包括点眼法及针灸疗法,临床上当审察病因,随证治之。现代医学对该病的治疗主要以缓解症状为主,寻找有效的中医治疗手段在现代临床应用中意义重大。     

Supervised methods for symptom name recognition in free-text clinical records of traditional Chinese medicine: An empirical study

Clinical records of traditional Chinese medicine (TCM) are documented by TCM doctors during their routine diagnostic work. These records contain abundant knowledge and reflect the clinical experience of TCM doctors. In recent years, with the modernization of TCM clinical practice, these clinical records have begun to be digitized. Data mining (DM) and machine learning (ML) methods provide an opportunity for researchers to discover TCM regularities buried in the large volume of clinical records. There has been some work on this problem. Existing methods have been validated on a limited amount of manually well-structured data. However, the contents of most fields in the clinical records are unstructured. As a result, the previous methods verified on the well-structured data will not work effectively on the free-text clinical records (FCRs), and the FCRs are, consequently, required to be structured in advance. Manually structuring the large volume of TCM FCRs is time-consuming and labor-intensive, but the development of automatic methods for the structuring task is at an early stage. Therefore, in this paper, symptom name recognition (SNR) in the chief complaints, which is one of the important tasks to structure the FCRs of TCM, is carefully studied. The SNR task is reasonably treated as a sequence labeling problem, and several fundamental and practical problems in the SNR task are studied, such as how to adapt a general sequence labeling strategy for the SNR task according to the domain-specific characteristics of the chief complaints and which sequence classifier is more appropriate to solve the SNR task. To answer these questions, a series of elaborate experiments were performed, and the results are explained in detail.     

建立中药材盲样检验机制 有效预防以权谋私

从建立管理制度、完善工作程序、编制作业文件、加强运行监督等方面介绍了药品检验机构新近运行的中药材盲样检验机制,详细介绍了中药材盲样检验工作流程,对中药材盲样检验机制在药品检验机构廉政建设中有效预防以权谋私的作用进行了简要论述。     

2002～2006年我院中药处方药名分析

目的:促进中药处方药名的规范化管理。方法:对我院2002～2006年中药处方药名进行分析。结果:中药处方药名存在同物异名,同名异物,炮制品不分,药用部位不明等现象。结论:中药处方药名应统一规范。