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18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)最新文献

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Supporting collaboration and information sharing in computer-based clinical guideline management 支持基于计算机的临床指南管理中的协作和信息共享
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.95
Kudakwashe Dube, Essam Mansour, Bing Wu
{"title":"Supporting collaboration and information sharing in computer-based clinical guideline management","authors":"Kudakwashe Dube, Essam Mansour, Bing Wu","doi":"10.1109/CBMS.2005.95","DOIUrl":"https://doi.org/10.1109/CBMS.2005.95","url":null,"abstract":"Collaboration and information sharing for facilitating patient and clinician mobility is important to consider in supporting computer-based clinical guidelines and protocols. This paper presents part of ongoing work to develop a generic approach to supporting information sharing and collaboration in computer-based clinical guideline management. A framework for guideline management is presented with enhancements for supporting collaboration and information sharing. The generic approach combines the active rule paradigm and XML technologies to create the basis for supporting collaboration and sharing in a distributed healthcare environment.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126536674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Biomedical Informatics Research Network: integrating multi-site neuroimaging data acquisition, data sharing and brain morphometric processing 生物医学信息学研究网络:集多站点神经影像数据采集、数据共享和脑形态测量处理于一体
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.38
J. Jovicich, M. Beg, Steve Pieper, C. Priebe, M. Miller, R. Buckner, B. Rosen
{"title":"Biomedical Informatics Research Network: integrating multi-site neuroimaging data acquisition, data sharing and brain morphometric processing","authors":"J. Jovicich, M. Beg, Steve Pieper, C. Priebe, M. Miller, R. Buckner, B. Rosen","doi":"10.1109/CBMS.2005.38","DOIUrl":"https://doi.org/10.1109/CBMS.2005.38","url":null,"abstract":"The Biomedical Informatics Research Network (BIRN) is a National Institutes of Health (USA) initiative that fosters distributed collaborations in biomedical science by utilizing information technology innovations. Morphometry BIRN is one of its testbeds and has the goal to develop the ability to conduct clinical imaging studies across multiple sites, to analyze structural imaging data with the most powerful software regardless of development site, and to test new hypotheses on large collections of subjects with well-characterized image and clinical data. Through large-scale analyses of patient population data acquired and pooled across sites, we are investigating neuroanatomic correlates of Alzheimer's Disease Depression and Mild Cognitive Impairment subjects. This paper describes progress in multi-site image calibration and in software integration for multi-site image processing.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129411806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 18
A missing data estimation analysis in type II diabetes databases 2型糖尿病数据库中缺失的数据估计分析
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.13
M. Giardina, Yongyang Huo, F. Azuaje, P. Mccullagh, R. Harper
{"title":"A missing data estimation analysis in type II diabetes databases","authors":"M. Giardina, Yongyang Huo, F. Azuaje, P. Mccullagh, R. Harper","doi":"10.1109/CBMS.2005.13","DOIUrl":"https://doi.org/10.1109/CBMS.2005.13","url":null,"abstract":"Type II diabetes is one of the most common causes of disability and death in the United Kingdom. This investigation analysed data acquired from diabetic patients at the Ulster Hospital in Northern Ireland in terms of statistical descriptive indicators and missing values. Such data are noisy and incomplete. This paper reports a comprehensive missing data estimation analysis. Five missing value imputation methods were compared, including k-Nearest Neighbours (k-NN) and correlation-based estimation models. From this analysis it can be concluded that a feature-based correlation method known as EMImpute/spl I.bar/Columns is a promising approach to estimating missing values. Nevertheless, k-NN methods may be useful to provide relatively accurate estimations with lower error variability. These estimation techniques will support the implementation of supervised and unsupervised learning tools for coronary heart disease risk assessment, a major complication of diabetes.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132247814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Incremental learning of ensemble classifiers on ECG data 心电数据集成分类器的增量学习
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.69
Jan Macek
{"title":"Incremental learning of ensemble classifiers on ECG data","authors":"Jan Macek","doi":"10.1109/CBMS.2005.69","DOIUrl":"https://doi.org/10.1109/CBMS.2005.69","url":null,"abstract":"We develop novel methods of incremental learning based on the bagging and boosting approaches to ensemble learning. Our method combines perceptron decision trees obtained with a margin maximizing algorithm into an ensemble in an incremental way. We demonstrate practical functionality of our algorithm on the task of ECG records classification. Our results are promising since comparable or superior accuracy is achieved when compared with results obtained by other existing methods of classification of ECG records, namely with the C5.0 decision tree algorithm.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113965512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 19
Relevance feedback for spine X-ray retrieval 脊柱x线检索的相关反馈
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.94
Xiaoqian Xu, D. J. Lee, Sameer Kiran Antani, L. Long
{"title":"Relevance feedback for spine X-ray retrieval","authors":"Xiaoqian Xu, D. J. Lee, Sameer Kiran Antani, L. Long","doi":"10.1109/CBMS.2005.94","DOIUrl":"https://doi.org/10.1109/CBMS.2005.94","url":null,"abstract":"Relevance feedback (RF) has been an active research area in content-based image retrieval (CBIR). RF intends to bridge the gap between the low-level image features and the high-level human visual perception by analyzing and employing the feedback information provided by the user. This gap becomes more evident and important in medical image retrieval due to the two distinct facts with regard to medical images: (1) subtle differences between images, even between pathological and non-pathological images; (2) subjective and different diagnosis even among experts. This paper describes a novel linear weight-updating approach for RF applying to spine X-ray image retrieval. The algorithm utilizes both positive and negative examples to gain feedback from the user. Experimental results show that the proposed approach can substantially improve the retrieval performance to better satisfy the individual user's preferences.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"09 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127219536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 16
A novel computational analysis of heterogeneity in breast tissue 一种新的乳腺组织异质性计算分析
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.16
S. Maskery, Yonghong Zhang, R. Jordan, Hai Hu, C. Shriver, J. Hooke, M. Liebman
{"title":"A novel computational analysis of heterogeneity in breast tissue","authors":"S. Maskery, Yonghong Zhang, R. Jordan, Hai Hu, C. Shriver, J. Hooke, M. Liebman","doi":"10.1109/CBMS.2005.16","DOIUrl":"https://doi.org/10.1109/CBMS.2005.16","url":null,"abstract":"Breast cancer presents as part of a heterogeneous mix of breast disease pathologies whose biological origins are poorly understood. A systematic and quantitative study of heterogeneity in breast tissue would enable us to characterize the disease states present, and use that characterization to guide further research into the complex pathologic associations within breast tissue and between patients. Initially we focus on characterizing the co-occurrence of breast pathology-related diagnoses. In particular, this abstract presents our initial results from characterizing the co-occurrence of double and triple diagnoses. We will expand this analysis to co-occurrence of larger diagnosis sets. Additionally, we plan to analyze co-occurrence with other types of patient information, including: socio-economic status, family history, lifestyle choices, co-morbidity with other diseases, and many other factors hypothesized to contribute to an increased risk for developing breast cancer.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127258865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Classification of the auditory brainstem response (ABR) using wavelet analysis and Bayesian network 基于小波分析和贝叶斯网络的听觉脑干反应分类
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.41
Rui Zhang, Gerry McAllister, B. Scotney, S. McClean, G. Houston
{"title":"Classification of the auditory brainstem response (ABR) using wavelet analysis and Bayesian network","authors":"Rui Zhang, Gerry McAllister, B. Scotney, S. McClean, G. Houston","doi":"10.1109/CBMS.2005.41","DOIUrl":"https://doi.org/10.1109/CBMS.2005.41","url":null,"abstract":"The auditory brainstem response (ABR) has become a routine clinical tool for hearing and neurological assessment. In order to pick out the ABR from the background EEG activity that obscures it, stimulus-synchronized averaging of many repeated trials is necessary and it typically requires up to 2000 repetitions. This number of repetitions can be very difficult, time consuming and uncomfortable for some subjects. In this study a method combining the wavelet analysis and the Bayesian network is introduced to reduce the required number of repetitions, which could offer a great advantage in the clinical situation. The important features of the ABR are extracted by thresholding and matching the wavelet coefficients. These extracted features are then used as the variables to build up the Bayesian network for classifying the ABR. 172 ABRs with 64 repetitions are applied in this study to learn the Bayesian network and estimate the conditional probability tables (CPTs). A further 142 ABRs with 64 repetitions are used to test the network. Moreover, this Bayesian network can also be applied to classify the ABRs with 128 repetitions.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127439014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
A Practical Tool for Visualizing and Data Mining Medical Time Series 可视化和数据挖掘医疗时间序列的实用工具
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.17
Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamonn J. Keogh, S. Lonardi, C. Ratanamahatana, H. V. Herle
{"title":"A Practical Tool for Visualizing and Data Mining Medical Time Series","authors":"Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamonn J. Keogh, S. Lonardi, C. Ratanamahatana, H. V. Herle","doi":"10.1109/CBMS.2005.17","DOIUrl":"https://doi.org/10.1109/CBMS.2005.17","url":null,"abstract":"The increasing interest in time series data mining has had surprisingly little impact on real world medical applications. Practitioners who work with time series on a daily basis rarely take advantage of the wealth of tools that the data mining community has made available. In this work, we attempt to address this problem by introducing a parameter-light tool that allows users to efficiently navigate through large collections of time series. Our approach extracts features from a time series of arbitrary length and uses information about the relative frequency of these features to color a bitmap in a principled way. By visualizing the similarities and differences within a collection of bitmaps, a user can quickly discover clusters, anomalies, and other regularities within the data collection. We demonstrate the utility of our approach with a set of comprehensive experiments on real datasets from a variety of medical domains","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117278546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 25
Medical imaging and osteoporosis: fractal's lacunarity analysis of trabecular bone in MR images 医学影像与骨质疏松:MR图像中骨小梁的分形间隙分析
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.73
A. Zaia, Roberta Eleonori, P. Maponi, R. Rossi, R. Murri
{"title":"Medical imaging and osteoporosis: fractal's lacunarity analysis of trabecular bone in MR images","authors":"A. Zaia, Roberta Eleonori, P. Maponi, R. Rossi, R. Murri","doi":"10.1109/CBMS.2005.73","DOIUrl":"https://doi.org/10.1109/CBMS.2005.73","url":null,"abstract":"The aim of this study was to develop a method of MR image analysis able to provide parameter(s) sensitive to bone microarchitecture changes in aging and osteoporosis onset and progression. The method has been built taking into account fractal properties of many anatomic and physiologic structures. Fractal lacunarity analysis has been used to determine relevant parameter(s) to differentiate among three types of trabecular bone structure (healthy young, healthy perimenopaused, and osteoporotic patients) from lumbar vertebra MR images. In particular, we propose to approximate the lacunarity function by a hyperbola model function, that depends on three different coefficients, /spl alpha/, /spl beta/, /spl gamma/, and to compute these coefficients as the solution of a least squares problem. This term of coefficients provides the model function that better represents the variation of mass density of pixels in the image considered. Clinical application of this preliminary version of our method suggests that one of the three coefficients, namely /spl beta/, may represent a standard for an evaluation of trabecular bone architecture and a potential useful parametric index in early diagnosis of osteoporosis.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128136560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 23
The Telescience project: application to middleware interaction components Telescience项目:应用程序到中间件交互组件
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.99
A. Lin, L. Dai, K. Ung, S. Peltier, Mark Ellisman
{"title":"The Telescience project: application to middleware interaction components","authors":"A. Lin, L. Dai, K. Ung, S. Peltier, Mark Ellisman","doi":"10.1109/CBMS.2005.99","DOIUrl":"https://doi.org/10.1109/CBMS.2005.99","url":null,"abstract":"The Telescience Project/spl trade/ (https://telescience.ucsd.edu) aims to provide a complete, end-to-end, single sign-on solution for biomedical image analysis and structure-function correlation. Telescience merges advanced solutions for remote instrumentation (via Telemicroscopy/spl trade/), distributed data computation and storage, and transparent access to federated databases of cell structure. Here, we describe the Grid-based system architecture that enables the Telescience Project. This Grid service architecture provides a fabric for seamless interoperability among user interfaces (Web portals and applications) and externally addressable Grid resources (instruments and computers). Although many software components and tools provide some capabilities relating to enabling usable scientific grids, few systems offer the required complete interactions with grid infrastructures \"out of the box\". Significant time and effort, therefore, are needed for software evaluation, testing, and integration. Here we describe an emerging layer of the overall Grid infrastructure that provides a complete solution for application and portal developers to interact with core Grid functionality.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"13 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129327641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 19
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