{"title":"Exploratory temporal data mining process in hospital information systems","authors":"S. Tsumoto, H. Iwata, S. Hirano, Y. Tsumoto","doi":"10.1109/ICCI-CC.2012.6311140","DOIUrl":null,"url":null,"abstract":"This paper proposes an exploratory temporal data mining process which aims at capturing behavior of medical staff. The process consists of the following four process. First, datasets will be extracted from hospital information systems through double-step datawarehousing. Second, similarities between temporal sequences are calculated from datasets. Third, data mining methods such as clustering, multidimensional scaling are applied for obtaining the class labels. Finally, other data mining methods, such as decision tree and correspondence analysis are applied to original data sets with the class labels.","PeriodicalId":427778,"journal":{"name":"2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCI-CC.2012.6311140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper proposes an exploratory temporal data mining process which aims at capturing behavior of medical staff. The process consists of the following four process. First, datasets will be extracted from hospital information systems through double-step datawarehousing. Second, similarities between temporal sequences are calculated from datasets. Third, data mining methods such as clustering, multidimensional scaling are applied for obtaining the class labels. Finally, other data mining methods, such as decision tree and correspondence analysis are applied to original data sets with the class labels.