医学语言与临床数据标准化概述简

医学语言丰富多样,临床数据范围广泛且种类繁多。在信息技术已成为被普遍采用的医疗服务辅助工具的今天,如果缺乏标准化的数据定义,就会导致计算机数据调用、分析过程和结果出现混乱。面对临床过程产生的大量叙述性文本数据,自然语言处理技术的应用面临巨大挑战,因此,需要以统一、标准化的形式表达医学概念,即通过构建和应用临床信息模型、标准医学术语、编码系统,形成计算机可识别和处理的结构化、代码化数据,支持信息技术在临床决策中发挥作用,同时促进临床信息的二次利用。     

噪声对作业工人血脂影响的研究

目的为了了解噪声对作业工人血脂的影响。方法选择某石化公司232名接触噪声的外操人员为噪声组,该公司294名不接触噪声的内操人员为对照组,用t检验和χ2检验对血脂水平进行统计学分析。结果噪声组工人血脂成分中TG含量均值与对照组相比,差异具有统计学意义(t=-2.79,P0.01);CHO含量均值两组相比差异没有统计学意义(P0.05)。噪声组TG异常检出率与对照组相比,差异具有统计学意义(t=3.97,P0.05);CHO异常检出率两组相比差异无统计学意义(P0.05)。结论噪声对人体血脂水平的影响尚需作进一步的研究和探讨。     

Detecting rare events using extreme value statistics applied to epileptic convulsions in children

ObjectiveNocturnal home monitoring of epileptic children is often not feasible due to the cumbersome manner of seizure detection with the standard method of video electroencephalography monitoring. The goal of this paper is to propose a method for hypermotor seizure detection based on accelerometers that are attached to the extremities.MethodsSupervised methods that are commonly used in literature need annotation of data and hence require expert (neurologist) interaction resulting in a substantial cost. In this paper an unsupervised method is proposed that uses extreme value statistics and seizure detection based on a model of normal behavior that is estimated using all recorded and unlabeled data. In this way the expensive interaction can be avoided.ResultsWhen applying this method to a labeled dataset, acquired from 7 patients, all hypermotor seizures are detected in 5 of the 7 patients with an average positive predictive value (PPV) of 53%. For evaluating the performance on an unlabeled dataset, seizure events are presented to the system as normal movement events. Since hypermotor seizures are rare compared to normal movements, the very few abnormal events have a negligible effect on the quality of the model. In this way, it was possible to evaluate the system for 3 of the 7 patients when 3% of the training set was composed of seizure events. This resulted in sensitivity scores of 80%, 22% and 90% and a PPV of 89%, 21% and 44% respectively. These scores are comparable with a state-of-the-art supervised machine learning based approach which requires a labeled dataset.ConclusionsA person-dependent epileptic seizure detection method has been designed that requires little human interaction. In contrast to traditional machine learning approaches, the imbalance of the dataset does not cause substantial difficulties.     

Clinical Social Networking—A New Revolution in Provider Communication and Delivery of Clinical Information across Providers of Care?

The adoption of social media technologies appears to enhance clinical outcomes through improved communications as reported by Bacigalupe (Fam Syst Heal 29(1):1-14, 2011). The ability of providers to more effectively, directly, and rapidly communicate among themselves as well as with patients should strengthen collaboration and treatment as reported by Bacigalupe (Fam Syst Heal 29(1):1-14, 2011). This paper is a case study in one organization's development of an internally designed and developed social technology solution termed “Unite.” The Unite system combines social technologies' features including push notifications, messaging, community groups, and user lists with clinical workflow and applications to construct dynamic provider networks, simplify communications, and facilitate clinical workflow optimization. Modeling Unite as a social technology may ease adoption barriers. Developing a social network that is integrated with healthcare information systems in the clinical space opens the doors to capturing and studying the way in which providers communicate. The Unite system appears to have the potential to breaking down existing communication paradigms. With Unite, a rich set of usage data tied to clinical events may unravel alternative networks that can be leveraged to advance patient care.     

The National Cancer Informatics Program (NCIP) Annotation and Image Markup (AIM) Foundation Model

Knowledge contained within in vivo imaging annotated by human experts or computer programs is typically stored as unstructured text and separated from other associated information. The National Cancer Informatics Program (NCIP) Annotation and Image Markup (AIM) Foundation information model is an evolution of the National Institute of Health’s (NIH) National Cancer Institute’s (NCI) Cancer Bioinformatics Grid (caBIG®) AIM model. The model applies to various image types created by various techniques and disciplines. It has evolved in response to the feedback and changing demands from the imaging community at NCI. The foundation model serves as a base for other imaging disciplines that want to extend the type of information the model collects. The model captures physical entities and their characteristics, imaging observation entities and their characteristics, markups (two- and three-dimensional), AIM statements, calculations, image source, inferences, annotation role, task context or workflow, audit trail, AIM creator details, equipment used to create AIM instances, subject demographics, and adjudication observations. An AIM instance can be stored as a Digital Imaging and Communications in Medicine (DICOM) structured reporting (SR) object or Extensible Markup Language (XML) document for further processing and analysis. An AIM instance consists of one or more annotations and associated markups of a single finding along with other ancillary information in the AIM model. An annotation describes information about the meaning of pixel data in an image. A markup is a graphical drawing placed on the image that depicts a region of interest. This paper describes fundamental AIM concepts and how to use and extend AIM for various imaging disciplines.     

基于MATLAB的CGMS数据整合分析软件的开发和在糖尿病合并低血糖时血糖波动特点研究上的使用

目的：观察低血糖血糖波动趋势,探究低血糖发生的特点。方法：通过矩阵实验室（MarxLabomtory,MATLAB）编程设计了与MmiMed解决方案（MiniMedSolutionsCGMSSensor,MSCS）的接口,利用MATLAB分析能力,实现大样本量的CGMS数据整合分析。结果：对829例CGMS数据进行筛选,符合研究条件405例,其中出现低血糖患者204例占50．62％。CGMS血糖监测系统与指测血糖在不同血糖范围均有较高一致性（P〈O．01）。低血糖患者整体血糖低于非低血糖患者,低血糖发生时间尤以半夜及午餐前居多。低血糖聚集发生时间平均在1点09分,标准差时间为5小时31分。不同年龄段低血糖患者比较．低血糖发生时间随年龄增长而提前（P〈O．01）。结论：MATLAB在大量CGMS监测数据处理具有速度快、设计灵活、使用方便等优点。低血糖的发生具有规律性,我们今后的研究方向是和低血糖发生可能相关的方向调节激素,神经内分泌的调节和脑生物钟的变化。     

1 + 1 = 3? The systematic development of a theoretical and evidence-based tailored multimedia intervention to improve medication adherence

ObjectiveTo describe the development of a theoretical and evidence-based tailored multimedia intervention to improve medication intake behavior in patients with inflammatory bowel disease (IBD). The intervention integrates interpersonal and technology-mediated strategies with the expectation that this will work synergistically.MethodsThe development followed the Medical Research Council's framework. Three literature reviews and three pre-tests among 84 IBD patients and eight nurses were conducted to guide the development of the intervention. A feasibility study was carried out among four nurses and 29 patients.ResultsThe components include: (1) an online preparatory assessment (OPA); (2) tailored interpersonal communication; and (3) tailored text messaging. To support the development, the feasibility was tested. Results indicated that the OPA was comprehensive and could be a helpful tool for both patients and nurses to prepare for the consultation. The training was evaluated as being instructive and applicable with a mean mark of 8.5. Of the developed messages, 65.6% received positive evaluations and were used in the intervention.ConclusionBy applying the framework, we were able to describe the logic behind the development of a tailored multimedia intervention to improve medication intake behavior.Practice implicationsThis study could serve as a guide for the development of other health interventions.