课程文献中心 更多>>

关键词： 数字信息   中华医学会   发表论文   杂志   object   管理系统   互联网   分布式  

摘要： 数字对象标识符（digital object identifier，DOI）是对包括互联网信息在内的数字信息进行标识的一种工具，是一个可供全球期刊快速链接的管理系统，整个系统由国际DOI基金会（IDF）进行全球分布式管理。

关键词： C语言   标识符   语法错误  

摘要： C语言是程序设计常用语言之一,它功能强大,语法简洁、紧凑,使用方便灵活。结合教学实践分析C语言中常见的错误,给出相应的解决方法,帮助初学者更好掌握C语言。

关键词： Android系统   智能终端识别   隐性标识符   指纹匹配算法  

摘要： 针对现有Android智能终端识别直接利用IMEI,Android_ID等显性标识符存在依赖敏感权限和易失效的问题,提出了一种基于隐性标识符组合的零权限设备识别方法.通过调用系统API并执行Linux Shell命令,从物理层、应用层以及用户层3个层次上获取设备型号、屏幕信息、内核编译信息、User Agent、系统语言、字体大小、字体列表、用户安装程序列表等8个隐性标识符,并将其组合形成设备指纹.然后,提出了指纹精确匹配算法和变化指纹关联匹配算法,用于仅1个隐性标识符发生变化且变化前后相似程度大于0.85时的设备关联识别.通过采集真实用户数据进行实验验证,结果表明所提算法的设备识别准确率达到94.52%.

关键词： 数字信息   中华医学会   发表论文   杂志   object   管理系统   互联网   分布式  

摘要： 数字对象标识符（digital object identifier，DOI）是对包括互联网信息在内的数字信息进行标识的一种工具，是一个可供全球期刊快速链接的管理系统，整个系统由国际DOI基金会（IDF）进行全球分布式管理。

关键词： 数字信息   中华医学会   标注   杂志   object   出版物   国际标准   条形码  

摘要： 数字对象唯一标识符（digital object identifier，DOI）是对包括互联网信息在内的数字信息进行标识的一种工具。在传统的出版物中，书刊、磁带、光盘都有国际标准编号（ISBN、ISSN、ISCN）及其条形码，作为出版物的唯一标识。这些标识使出版物得到有效的管理，便于读者查找和利用。而网上的文档一旦变更了网址便无从追索。数字信息标注DOI如同出版物的条形码，是一个永久和唯一的标识号。

关键词： 国际标准化组织   中国香港   注册中心   标识符   关联   国家标准   信息内容   底层技术  

摘要： 5月15日，基于我国国家标准研制的《国际标准关联标识符（ISLI）》国际标准由国际标准化组织（ISO）正式发布。同时，ISO宣布已将ISLI国际注册中心的承办权授予总部位于中国香港的国际信息内容产业协会（ICIA），这也是首个落户中国的国际标准注册中心。ISLI国际标准是基于我国《多媒体印刷读物（MPR）》国家标准及其底层技术，由中国新闻出版研究院、深圳市天朗时代科技有限公司等单位共同提出提案，于2011年4月在ISO获准立项的。

关键词： Machine learning   Multi-label classification   Privacy-preserving data mining  

摘要： Our study considers identification of demographic attributes of patients as a multi-label learning problem. This is a novel approach to predict accuracy of classification of patients' quasi-identifiers (race and gender attributes). To classify the sets of attributes, we applied ensembles of several multi-label learning algorithms. The best-performing multi-label ensembles include decision tree algorithms. In the empirical part of this study, we used on the UCI diabetics dataset of over 100,000 records, collected from 130 US hospitals. The dataset consisted of attributes that included patient demographics (race, gender, age), diagnoses code, lab results, etc. Experiments conducted on datasets of 1000, 10,000, 20,000 examples show that the best classifier achieves a high overall accuracy of 0.533 (1000 examples), 0.702 (10,000 examples), 0.569 (20,000 examples), improving over the baseline majority class classification which achieved accuracy of 0.526, 0.586, 0.562, respectively. Our approach can be further integrated into privacy-preserving data mining, where it can be used to assess risk of identification of different groups of individuals within a large data set.

关键词： Optical coherence tomography   Segmentation   Intravascular   Classification   Orthogonal least squares   Bifurcation   Machine learning  

摘要： Intravascular optical coherence tomography (IV-OCT) is an in-vivo imaging modality based on the intravascular introduction of a catheter which provides a view of the inner wall of blood vessels with a spatial resolution of 10-20 mu m. Recent studies in IV-OCT have demonstrated the importance of the bifurcation regions. Therefore, the development of an automated tool to classify hundreds of coronary OCT frames as bifurcation or nonbifurcation can be an important step to improve automated methods for atherosclerotic plaques quantification, stent analysis and co-registration between different modalities. This paper describes a fully automated method to identify IV-OCT frames in bifurcation regions. The method is divided into lumen detection;feature extraction;and classification, providing a lumen area quantification, geometrical features of the cross-sectional lumen and labeled slices. This classification method is a combination of supervised machine learning algorithms and feature selection using orthogonal least squares methods. Training and tests were performed in sets with a maximum of 1460 human coronary OCT frames. The lumen segmentation achieved a mean difference of lumen area of 0.11 mm(2) compared with manual segmentation, and the AdaBoost classifier presented the best result reaching a F-measure score of 97.5% using 104 features. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Algorithms   Clinical Trials, Phase III as Topic   Databases, Factual*   Humans   Information Storage and Retrieval*   Leukemia, Myeloid, Acute   Leukemia, Myeloid, Acute   Medical Oncology*   Pediatrics*   Reproducibility of Results  

摘要： Purpose Clinical trials data from National Cancer Institute (NCI)-funded cooperative oncology group trials could be enhanced by merging with external data sources. Merging without direct patient identifiers would provide additional patient privacy protections. We sought to develop and validate a matching algorithm that uses only indirect patient identifiers. Methods We merged the data from two Phase III Children's Oncology Group (COG) trials for de novo acute myeloid leukemia (AML) with the Pediatric Health Information Systems (PHIS). We developed a stepwise matching algorithm that used indirect identifiers including treatment site, gender, birth year, birth month, enrollment year and enrollment month. Results from the stepwise algorithm were compared against the direct merge method that used date of birth, treatment site, and gender. The indirect merge algorithm was developed on AAML0531 and validated on AAML1031. Results Of 415 patients enrolled on the AAML0531 trial at PHIS centers, we successfully matched 378 (91.1%) patients using the indirect stepwise algorithm. Comparison to the direct merge result suggested that 362 (95.7%) matches identified by the indirect merge algorithm were concordant with the direct merge result. When validating the indirect stepwise algorithm using the AAML1031 trial, we successfully matched 157 out of 165 patients (95.2%) and 150 (95.5%) of the indirectly merged matches were concordant with the directly merged matches. Conclusions These data demonstrate that patients enrolled on COG clinical trials can be successfully merged with PHIS administrative data using a stepwise algorithm based on indirect patient identifiers. The merged data sets can be used as a platform for comparative effectiveness and cost effectiveness studies.

关键词： Molecular structure   Chemical databases   Non-systematic chemical identifiers   Chemical name ambiguity   Quality control  

摘要： Background: A wide range of chemical compound databases are currently available for pharmaceutical research. To retrieve compound information, including structures, researchers can query these chemical databases using non-systematic identifiers. These are source-dependent identifiers (e.g., brand names, generic names), which are usually assigned to the compound at the point of registration. The correctness of non-systematic identifiers (i.e., whether an identifier matches the associated structure) can only be assessed manually, which is cumbersome, but it is possible to automatically check their ambiguity (i.e., whether an identifier matches more than one structure). In this study we have quantified the ambiguity of non-systematic identifiers within and between eight widely used chemical databases. We also studied the effect of chemical structure standardization on reducing the ambiguity of non-systematic identifiers. Results: The ambiguity of non-systematic identifiers within databases varied from 0.1 to 15.2 % (median 2.5 %). Standardization reduced the ambiguity only to a small extent for most databases. A wide range of ambiguity existed for non-systematic identifiers that are shared between databases (17.7-60.2 %, median of 40.3 %). Removing stereochemistry information provided the largest reduction in ambiguity across databases (median reduction 13.7 percentage points). Conclusions: Ambiguity of non-systematic identifiers within chemical databases is generally low, but ambiguity of non-systematic identifiers that are shared between databases, is high. Chemical structure standardization reduces the ambiguity to a limited extent. Our findings can help to improve database integration, curation, and maintenance.