Ref HAL: inserm-00711845_v1
PMID 22455759
DOI: 10.1186/1472-6963-12-82
Résumé: ABSTRACT: BACKGROUND: Although the management of sarcoma is improving, non adherence to clinical practice guidelines (CPGs) remains high, mainly because of the low incidence of the disease and the variety of histological subtypes. Since little is known about the health economics of sarcoma, we undertook a cost-effectiveness analysis (within the CONnective TIssue CAncer NETwork, CONTICANET) comparing costs and outcomes when clinicians adhered to CPGs and when they did not. METHODS: Patients studied had a histological diagnosis of sarcoma, were older than 15 years, and had been treated in the Rhone-Alpes region of France (in 2005/2006) or in the Veneto region of Italy (in 2007). Data collected retrospectively for the three years after diagnosis were used to determine relapse free survival and health costs (adopting the hospital's perspective and a microcosting approach). All costs were expressed in euros at their 2009 value. A 4% annual discount rate was applied to both costs and effects. The incremental cost-effectiveness ratio (ICER) was expressed as cost per relapse-free year gained when management was compliant with CPGs compared with when it was not. To capture uncertainty surrounding ICER, a probabilistic sensitivity analysis was performed based on a non-parametric bootstrap method. RESULTS: A total of 219 patients were included in the study. Compliance with CPGs was observed for 118 patients (54%). Average total costs reached 23,571 euros when treatment was in accordance with CPGs and 27,313 euros when it was not. In relation to relapse-free survival, compliance with CPGs strictly dominates non compliance, i.e. it is both less costly and more effective. Taking uncertainty into account, the probability that compliance with CPGs still strictly dominates was 75%. CONCLUSIONS: Our findings should encourage physicians to increase their compliance with CPGs and healthcare administrators to invest in the implementation of CPGs in the management of sarcoma.

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Ref HAL: hal-00712590_v1
DOI: 10.1016/j.eswa.2012.04.040
Résumé: In this paper, we present CatViz—Temporally-Sliced Correspondence Analysis Visualization. This novel method visualizes relationships through time and is suitable for large-scale temporal multivariate data. We couple CatViz with clustering methods, whereupon we introduce the concept of final centroid transfer, which enables the correspondence of clusters in time. Although CatViz can be used on any type of temporal data, we show how it can be applied to the task of exploratory visual analysis of text collections. We present a successful concept of employing feature-type filtering to present different aspects of textual data. We performed case studies on large collections of French and English news articles. In addition, we conducted a user study that confirms the usefulness of our method. We present typical tasks of exploratory text analysis and discuss application procedures that an analyst might perform. We believe that CatViz is general and highly applicable to large data sets because of its intuitiveness, effectiveness, and robustness. We expect that it will enable a better understanding of texts in huge historical archives.

Ref HAL: hal-00712547_v1
DOI: 10.1007/s10796-012-9405-6
Résumé: Today, the Web is the largest source of information in the world. There is currently an increasing demand that decision-making applications such as Data Warehousing (DW) and Business Intelligence (BI) move onto the Web, especially in the cloud. Integrating data into the DW/BI applications is still the most critical and time-consuming task. To make better decisions in DW/BI applications, next generation data integration poses new requirements to data integration systems, over those posed by traditional data integration. From these requirements is to integrate data in real-time and autonomously with minimal user intervention. Therefore, we propose in this paper a metadata-based, event-driven, and service-oriented framework for integrating real-time data autonomously. The framework utilizes Web standards to integrate data, from heterogeneous and distributed sources. It exploits the XML language to address data heterogeneity, Web services to tackle data distribution, and Active XML (AXML) to store integrated data. The framework is also subscribed to Web services for real-time change data capture. Moreover, beside logging different framework events into a specified repository for on-line analysis and reporting, we propose a novel Frequency XML-based Tree (FXT) structure for mining association rules from logged event streams using XQuery. The framework is also incorporates active rules to automate and activate different integration services. Finally, we have a web application prototype as a proof of concept.

Commentaires: Special issue on Business Intelligence and the Web

Résumé: Statistical comparisons for topological equivalence of proximity measures

Résumé: Topological comparisons of proximity measures

Résumé: Map generalization can be used as a central component of Spatial Decision Support Systems to provide a simplified and more readable cartographic visualization of geographic information. Indeed, it supports the user mental process for discovering important and unknown geospatial relations, trends and patterns. Spatial OLAP (SOLAP) integrates spatial data into OLAP and data warehouse systems. SOLAP models and tools are based on the concepts of spatial dimensions and measures that represent the axes and the subjects of the spatio-multidimensional analysis. Although powerful under some respect, current SOLAP models cannot support map generalization capabilities. This paper provides the first effort to integrate Map Generalization and OLAP. Firstly the authors define all modeling and querying requirements to do this integration, and then present a SOLAP model and algebra that support map generalization concepts. The approach extends SOLAP spatial hierarchies introducing multi-association relationships, supports imprecise measures, and it takes into account spatial dimensions constraints generated by multiple map generalization hierarchies.

Résumé: Complex Object-Based Multidimensional Modeling and Cube Construction In the International

Commentaires: Special issue on Warehousing and OLAPing Complex, Spatial and Spatio-Temporal Data