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

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Synopsis for microbiological data stream analysis 微生物数据流分析摘要
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.96
Gianfranco Cellarosi, Claudio Sartori
{"title":"Synopsis for microbiological data stream analysis","authors":"Gianfranco Cellarosi, Claudio Sartori","doi":"10.1109/CBMS.2005.96","DOIUrl":"https://doi.org/10.1109/CBMS.2005.96","url":null,"abstract":"This paper derives from the extensive analysis of the results of microbiological laboratory output in a large hospital. In this environment data items are automatically collected by transactions linked to the analysis devices and the data flow rate can be very high. In addition, the time of the data items is extremely relevant, since a variation of the number of positive findings can be generated by dangerous events, such as outbreaks. The typical setting of data mining applications is to process data, in search of some hidden information. Unfortunately in this environment, we have many transactions and everyone of these is a potentially important information. When the data set changes, some kind of re-computation, either from scratch or according to differences only, has to be done. Things change when the change rate increases, so as to make difficult to process changes before new changes arrive. We define this particular situation as a data stream, and we devise a framework allowing efficient analysis of data streams. We propose a base set of techniques, which can be used to analyze data streams in Euclidean space, putting together information processing and statistical techniques. In particular, we are interested in detecting \"alarms\" in microbiological time series, that is points in time where the detected data differ from the values expected on the basis of past history. We provide also experimental results, based on real and data.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"2 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":"116123007","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
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
Data mining methods supporting diagnosis of melanoma 支持黑色素瘤诊断的数据挖掘方法
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.46
J. Grzymala-Busse, Z. Hippe
{"title":"Data mining methods supporting diagnosis of melanoma","authors":"J. Grzymala-Busse, Z. Hippe","doi":"10.1109/CBMS.2005.46","DOIUrl":"https://doi.org/10.1109/CBMS.2005.46","url":null,"abstract":"Melanoma, a dangerous skin cancer, is usually diagnosed using the ABCD formula. The main objective of our research was to find a better formula resembling the original ABCD formula using four different discretization methods. All four corresponding modified ABCD formulas are significantly more accurate (with the level of significance 5%) than the original ABCD formula. Our additional objective was to calibrate the rule set induced from the original data set, describing melanoma, using the best discretization method, so that the sensitivity (the conditional probability for recognition of malignant and suspicious melanoma) was increased. This objective was accomplished using a technique of changing rule strengths.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"9 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":"133959893","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: 14
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
Predicting preterm birth using artificial neural networks 用人工神经网络预测早产
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.84
C. Catley, M. Frize, R. Walker, D. Petriu
{"title":"Predicting preterm birth using artificial neural networks","authors":"C. Catley, M. Frize, R. Walker, D. Petriu","doi":"10.1109/CBMS.2005.84","DOIUrl":"https://doi.org/10.1109/CBMS.2005.84","url":null,"abstract":"This paper has three contributions: 1) to evaluate how changing the a priori distribution of the training set affects the performance of a back-propagation feed-forward artificial neural network (ANN) in predicting PreTerm Birth (PTB) for obstetrical patients, 2) to assess the effectiveness of the weight elimination cost function in improving the ANN's classification of PTB and in identifying a new minimal dataset, and (3) to determine if PTB can be predicted outside of clinical trial situations using data readily available to the physician during obstetrical care. The ANN was trained and tested on cases with 8 input variables describing the patient's obstetrical history; the output variable was PTB before 37 weeks gestation. To observe the impact of training with a higher-than-normal prevalence, an artificial training set with a PTB rate of 23% was created. Networks trained on higher-than-normal prevalence achieved higher sensitivity rates and greater C-index values, at the cost of slightly lower specificity and correct classification rates.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"65 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":"125705228","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: 5
A data mining based approach for the EEG transient event detection and classification 基于数据挖掘的脑电瞬态事件检测与分类方法
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.7
T. Exarchos, A. Tzallas, D. Fotiadis, S. Konitsiotis, S. Giannopoulos
{"title":"A data mining based approach for the EEG transient event detection and classification","authors":"T. Exarchos, A. Tzallas, D. Fotiadis, S. Konitsiotis, S. Giannopoulos","doi":"10.1109/CBMS.2005.7","DOIUrl":"https://doi.org/10.1109/CBMS.2005.7","url":null,"abstract":"An automated methodology which detects transient events in EEG recordings and classifies those as epileptic spikes, muscle activity, eye blinking activity and sharp alpha activity is presented. It is based on data mining algorithms and includes four stages: (I) EEG preprocessing and transient events detection, (II) clustering of transient events and feature extraction, (III) feature discretization and (IV) association rule mining and classification. The methodology is evaluated using a dataset of 25 EEG recordings and the obtained overall accuracy is 84.35%. The major advantage of our approach is that it is able to provide interpretation for the decisions made since it is based on a set of association rules.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"64 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":"134231902","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: 14
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
Approximations to magic: finding unusual medical time series 近似魔法:发现不寻常的医疗时间序列
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.34
Jessica Lin, Eamonn J. Keogh, A. Fu, H. V. Herle
{"title":"Approximations to magic: finding unusual medical time series","authors":"Jessica Lin, Eamonn J. Keogh, A. Fu, H. V. Herle","doi":"10.1109/CBMS.2005.34","DOIUrl":"https://doi.org/10.1109/CBMS.2005.34","url":null,"abstract":"In this work we introduce the new problem of finding time series discords. Time series discords are subsequences of longer time series that are maximally different to all the rest of the time series subsequences. They thus capture the sense of the most unusual subsequence within a time series. While the brute force algorithm to discover time series discords is quadratic in the length of the time series, we show a simple algorithm that is 3 to 4 orders of magnitude faster than brute force, while guaranteed to produce identical results.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"68 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":"133463130","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: 138
Reducing the computational cost for statistical medical image analysis: an MRI study on the sexual morphological differentiation of the corpus callosum 减少统计医学图像分析的计算成本:胼胝体性别形态分化的MRI研究
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.93
D. Kontos, V. Megalooikonomou, J. Gee
{"title":"Reducing the computational cost for statistical medical image analysis: an MRI study on the sexual morphological differentiation of the corpus callosum","authors":"D. Kontos, V. Megalooikonomou, J. Gee","doi":"10.1109/CBMS.2005.93","DOIUrl":"https://doi.org/10.1109/CBMS.2005.93","url":null,"abstract":"We illustrate the application of intelligent medical image analysis techniques in order to reduce the computational cost of statistical voxel-wise analysis for detecting discriminative regions of morphological variability among different populations. We demonstrate that novel statistical image processing techniques that operate selectively on groups of pixels are suitable for morphological analysis of anatomical structures visualized by modern medical imaging modalities. We also show that the proposed methodology effectively decreases the number of statistical tests performed, alleviating the effect of the multiple comparison problem. We show that our approach detects regions of statistically significant morphological variability. Our results validate previous findings, while being robust across a wide range of experimental settings.","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":"130506486","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: 2
Challenges of ultra large scale integration of biomedical computing systems 超大规模生物医学计算系统集成的挑战
18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05) Pub Date : 2005-06-23 DOI: 10.1109/CBMS.2005.40
R. Begent, M. Brady, A. Finkelstein, D. Gavaghan, P. Kerr, H. Parkinson, F. Reddington, J. M. Wilkinson
{"title":"Challenges of ultra large scale integration of biomedical computing systems","authors":"R. Begent, M. Brady, A. Finkelstein, D. Gavaghan, P. Kerr, H. Parkinson, F. Reddington, J. M. Wilkinson","doi":"10.1109/CBMS.2005.40","DOIUrl":"https://doi.org/10.1109/CBMS.2005.40","url":null,"abstract":"The NCRI Informatics Initiative is overseeing the implementation of an informatics framework for the UK cancer research community. The framework advocates an integrated multidisciplinary method of working between scientific and medical communities. Key to this process is community adoption of high quality acquisition, storage, sharing and integration of diverse data elements to improve knowledge of the causes, prevention and treatment of cancer. The integration of the complex data and meta-data used by these multiple communities is a significant challenge and there are technical, resource-based and sociological issues to be addressed. In this paper we review progress aimed at establishing the framework and outline key challenges in ultra large scale integration of biomedical computing systems.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"158 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":"122983081","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
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