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Recent studies have illustrated historical financial data could be used to predict future revenues and profits. Prediction models would be accurate when long-run data that traces back for multiple years is available. However, changes in service structures often result in alteration of the nomenclatures of the services, making the streams of financial transactions associated with affected services...
This paper presents a proposal for a decision support system for the prevention of Intensive Care Unit readmissions, that is being built based on data from the MIMIC II database. The proposed system fuses the results of two distinct classification approaches, one based on available numerical data, and the other based on medical text annotations. The former uses neural fuzzy models and fuzzy modeling...
Laboratory testing is a frequent activity for patients in intensive care units (ICU). Recent studies demonstrate that frequent laboratory testing does not necessarily relate to better outcomes. We hypothesize that unnecessary laboratory testing can be reduced by predicting which tests are unlikely to influence clinical management. Reducing unnecessary tests could reduce morbidity and hospitalization...
In this article, the authors provide an example workflow-and a simple classification of user questions on the workflow's data products-to combine and interchange contextual metadata through a semantic data model and infrastructure. They also analyze their approach's potential to support enhanced semantic provenance applications.
Most predictive data mining methods are based on the assumption that the historical data involved in building and verifying a model are the best estimator of what will happen in the future. However, the relevance of past to the future depends on the application domain in a specific timeframe. In this paper, we present a method of predicting the future from temporal data using information decay technique...
In order to improve the efficiency of database management and intelligence of database record classification, a classification method of network database record based on fuzzy theory is proposed in this paper. Firstly, an automatic classification frame of database is constructed, and then standard record model and special data record and new record model on fuzzy set are given. By calculating the...
The paper deals with the problem of the detection of rare patterns in an unbalanced dataset related to an industrial problem concerning the identification of manufactured defective metal products on the basis of product and process parameters. Within this work several approaches have been attempted for the development of a classifier whose performance are able to meet the industrial requirements,...
Traditional data models explicitly or implicitly assume that data are organized according to a single, "correct" classification scheme. However, there is increasing recognition that biological and other phenomena can be classified in multiple ways to accommodate varying perspectives. In this context, we review an approach to instance-based data modeling that might be useful for managing...
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