D. Kyriazis, K. Tserpes, George Kousiouris, A. Menychtas, G. Katsaros, T. Varvarigou
{"title":"Data Aggregation and Analysis: A Grid-Based Approach for Medicine and Biology","authors":"D. Kyriazis, K. Tserpes, George Kousiouris, A. Menychtas, G. Katsaros, T. Varvarigou","doi":"10.1109/ISPA.2008.34","DOIUrl":null,"url":null,"abstract":"A constantly increasing number of applications from various scientific sectors are finding their way towards adopting grid technologies in order to take advantage of their capabilities: the advent of grid environments made feasible the solution of computational intensive problems in a reliable and cost-effective way. In this paper we present a grid-based approach for aggregation of data that are obtained from various sources (e.g. cameras, sensors) and their analysis with the use of genetic algorithms. By also taking into consideration general historical data and patient-specific medical information, we present the realization of the proposed approach with an application scenario for personalized healthcare and medicine.","PeriodicalId":345341,"journal":{"name":"2008 IEEE International Symposium on Parallel and Distributed Processing with Applications","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Symposium on Parallel and Distributed Processing with Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2008.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
A constantly increasing number of applications from various scientific sectors are finding their way towards adopting grid technologies in order to take advantage of their capabilities: the advent of grid environments made feasible the solution of computational intensive problems in a reliable and cost-effective way. In this paper we present a grid-based approach for aggregation of data that are obtained from various sources (e.g. cameras, sensors) and their analysis with the use of genetic algorithms. By also taking into consideration general historical data and patient-specific medical information, we present the realization of the proposed approach with an application scenario for personalized healthcare and medicine.