Huriviades Calderón-Gómez, A. Garcés-Jiménez, Miguel Vargas-Lombardo, J. Gómez-Pulido, M. Polo-Luque, J. Castillo, Gloria Sención, J. S. Moreno
{"title":"Proposal Using the Cloud Architecture in System for the Early Detection of Infectious Diseases in Elderly People Fed by Biosensors Records","authors":"Huriviades Calderón-Gómez, A. Garcés-Jiménez, Miguel Vargas-Lombardo, J. Gómez-Pulido, M. Polo-Luque, J. Castillo, Gloria Sención, J. S. Moreno","doi":"10.1109/IESTEC46403.2019.00118","DOIUrl":null,"url":null,"abstract":"A joint medical and computing research group has developed a full system to build a clinical database (DB) in the Cloud to extract knowledge for the speed diagnosis of infectious diseases. It is a significant step forward as traditionally the lack of data prevents the development of medical recommenders to anticipate the diagnosis. In addition, the steadily data update enables efficient telecare for individual patients, raising the satisfaction level of the patient and relatives. The usability of the system have been tested with satisfactory results.","PeriodicalId":388062,"journal":{"name":"2019 7th International Engineering, Sciences and Technology Conference (IESTEC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 7th International Engineering, Sciences and Technology Conference (IESTEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IESTEC46403.2019.00118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A joint medical and computing research group has developed a full system to build a clinical database (DB) in the Cloud to extract knowledge for the speed diagnosis of infectious diseases. It is a significant step forward as traditionally the lack of data prevents the development of medical recommenders to anticipate the diagnosis. In addition, the steadily data update enables efficient telecare for individual patients, raising the satisfaction level of the patient and relatives. The usability of the system have been tested with satisfactory results.