脑机接口技术在医疗领域的应用

脑机接口技术不依赖于常规大脑信息输出通路,而是建立了大脑与计算机等外部设备之间直接的信息交流和控制通道。该技术有广阔的应用前景,受到广泛关注。各国都相继提出了国家层面的脑计划,为脑机接口的发展提供政策指引和支持。分析总结了脑机接口技术的现状及其在医疗领域的应用,探讨了该技术面临的挑战、发展和建议。     

IT vendors’ legitimation strategies and market share: The case of EMR systems

This study investigates the legitimation strategies adopted by information technology (IT) vendors and their respective influence on market share. We conducted an analysis of the public discourse on websites of top Electronic Medical Record (EMR) vendors in Ontario, Canada. A total of 815 segments extracted from these websites were analyzed. Our findings indicate that strategies under the cognitive and pragmatic forms of legitimacy were strongly represented in the EMR vendors’ discourses compared with regulative and normative strategies. Furthermore, the link between legitimation strategies and market share has not yet been clearly established. Implications for practice and research are discussed.     

基于CRF模型的临床医嘱信息实体识别方法应用研究

将命名实体识别技术运用于临床业务系统中,实现对临床医嘱的实体识别,提高临床医疗的工作效率。以上海市胸科医院为研究背景,提出嵌入于临床业务信息系统的临床医嘱实体识别方法。基于历年医嘱数据建立专项语料词库,运用CRF模型进行实时实体识别。随着识别系统上线使用,共处理了8362条医嘱,实验结果表明其准确率较好,在信息支撑度方面提升了医护人员的满意度。医嘱实体识别技术能够有效提高执行效率和医疗质量,也为医疗领域的知识挖掘工作提供了参考依据。     

核电厂控制系统软件回归测试的分析与研究

回归测试是软件测试中的一个非常重要的过程,在软件生命周期的任何阶段都可能存在回归测试,合理地选择回归测试方案,证明已正确修改软件,保证软件测试的效率和有效性,提高软件质量是非常必要的。     

基于地铁制动系统的测试装置研究与开发

详细分析了地铁车辆电空制动系统的工作原理,提出了基于地铁制动系统的测试装置的设计方案。通过硬件设计及上、下位机软件程序设计,实现了对制动电子控制装置性能的检测。制动测试装置输出控制信号给工控机,接收信号处理单元采集的外部待测试设备脉冲信号。运行在工控机的上位机软件,负责人机交互。根据测试规程要求,对制动电子控制装置进行一系列自动测试,对测试结果评判后生成测试记录文件,成功实现对列车制动系统性能的现场测试。结果表明,该装置准确、可靠,具有重要的应用价值。     

基于PID算法的医用自动定位离心机控制系统设计

该文设计了搭建在医疗液体样本检验自动处理工作平台上的自动定位离心机控制系统。其主要功能是完成平台所需样本的自动抓取、自动放置和自动离心等。该系统利用槽型光电开关、增量型编码器、单片机以及增量式PID控制算法等,实现了离心机的精确定位、高速离心以及联机通讯控制等。与目前常用的医用离心机控制系统相比,该系统具有定位精度高、可免除人工参与、工作效率高等特点。     

基于大数据的掌上医疗器械检索平台研究

为了提高掌上医疗器械的信息化检索和管理能力,提出基于大数据的掌上医疗器械检索方法,构建掌上医疗器械检索的大数据分布模型,采用有向图模型构建掌上医疗器械信息库的检索节点分布结构模型,在掌上医疗器械信息库库中进行语义关联规则分析,采用字符串的匹配技术,建立掌上医疗器械信息库检索的模糊决策模型,采用大数据融合方法实现掌上医疗器械检索的算法设计,结合自相关特征匹配方法实现掌上医疗器械信息库的语义特征提取,实现掌上医疗器械检索平台的优化设计。仿真结果表明,采用该方法进行掌上医疗器械检索的智能性较好,检索的查准性较高,时延较低。     

中文症状知识库的建立与分析

构建大规模的知识库是人工智能、自然语言理解等领域的基础任务之一。症状作为描述病人的主观感受和诊断疾病的重要依据,更是优化智能导诊、医学问答等任务的重要因素。该文在现有的医学症状知识库研究的基础上,结合症状的概念、特征及在医学诊断中发挥的作用,构建了一个公开的中文症状知识库。该知识库从症状的本体分类、相关疾病、发作部位及多发人群等层面对相关属性进行了详细描述,涵盖了8 772种症状,共计146 631条属性关系。所构建的症状知识库(CSKB)是中文医学知识图谱的重要组成部分,并为KBQA、知识推理及决策支持等应用提供了数据基础。     

Visual Exploration of Dynamic Multichannel EEG Coherence Networks

Electroencephalography (EEG) coherence networks represent functional brain connectivity, and are constructed by calculating the coherence between pairs of electrode signals as a function of frequency. Visualization of such networks can provide insight into unexpected patterns of cognitive processing and help neuroscientists to understand brain mechanisms. However, visualizing dynamic EEG coherence networks is a challenge for the analysis of brain connectivity, especially when the spatial structure of the network needs to be taken into account. In this paper, we present a design and implementation of a visualization framework for such dynamic networks. First, requirements for supporting typical tasks in the context of dynamic functional connectivity network analysis were collected from neuroscience researchers. In our design, we consider groups of network nodes and their corresponding spatial location for visualizing the evolution of the dynamic coherence network. We introduce an augmented timeline‐based representation to provide an overview of the evolution of functional units (FUs) and their spatial location over time. This representation can help the viewer to identify relations between functional connectivity and brain regions, as well as to identify persistent or transient functional connectivity patterns across the whole time window. In addition, we introduce the time‐annotated FU map representation to facilitate comparison of the behaviour of nodes between consecutive FU maps. A colour coding is designed that helps to distinguish distinct dynamic FUs. Our implementation also supports interactive exploration. The usefulness of our visualization design was evaluated by an informal user study. The feedback we received shows that our design supports exploratory analysis tasks well. The method can serve as a first step before a complete analysis of dynamic EEG coherence networks.     

Interactive Volumetric Visual Analysis of Glycogen‐derived Energy Absorption in Nanometric Brain Structures

Digital acquisition and processing techniques are changing the way neuroscience investigation is carried out. Emerging applications range from statistical analysis on image stacks to complex connectomics visual analysis tools targeted to develop and test hypotheses of brain development and activity. In this work, we focus on neuroenergetics, a field where neuroscientists analyze nanoscale brain morphology and relate energy consumption to glucose storage in form of glycogen granules. In order to facilitate the understanding of neuroenergetic mechanisms, we propose a novel customized pipeline for the visual analysis of nanometric‐level reconstructions based on electron microscopy image data. Our framework supports analysis tasks by combining i) a scalable volume visualization architecture able to selectively render image stacks and corresponding labelled data, ii) a method for highlighting distance‐based energy absorption probabilities in form of glow maps, and iii) a hybrid connectivitybased and absorption‐based interactive layout representation able to support queries for selective analysis of areas of interest and potential activity within the segmented datasets. This working pipeline is currently used in a variety of studies in the neuroenergetics domain. Here, we discuss a test case in which the framework was successfully used by domain scientists for the analysis of aging effects on glycogen metabolism, extracting knowledge from a series of nanoscale brain stacks of rodents somatosensory cortex.