Project PROPHET : Brief report of preliminary results

viXra Pub Date : 2020-08-01 DOI:10.21203/rs.3.rs-58308/v1
A. Garyfallos
{"title":"Project PROPHET : Brief report of preliminary results","authors":"A. Garyfallos","doi":"10.21203/rs.3.rs-58308/v1","DOIUrl":null,"url":null,"abstract":"Forecasting forthcoming \"health events\" is an extremely challenging task for the Remote Patient Monitoring systems (RPM systems) sector, which relies in real time information and communication technologies. Remote patient monitoring is a medical service which includes following and observing patients that are not in the same location with their health care provider. In general, the patient is equipped with a “smart” monitoring device, and the recorded data (vital signs) are securely transmitted via telecommunication networks to the health care provider. Modern remote patient monitoring devices are small, discrete and easy to wear, allowing \"bearers\" to move freely and with comfort. In this framework, MOKAAL pc has developed the IFS_RPM service (Integrated Facilitation Services for Remote Patient Monitoring) supplying the necessary ICT infrastructure, which is necessary for the provision of the RPM services. Following the completion of IFS_RPM project, MOKAAL pc launched a research project under the code name \"PROPHETTM\" . PROPHETTM main objective is to investigate the possibilities of introducing a real time predicting model based on remotely collected vital signs, that would utilize time series of metric data in conjunction with the information stored in the Electronic Health Records (EHR) of the \"bearer\", attempting to predict in real time, the probability of a \"health event\" occurring in the near future. To meet this objective, the PROPHETTM project team designed an evolutionary prototype of the \"health event\" forecasting model, which was developed and tested in a laboratory environment and it will be upgraded to a working prototype to be tested in real conditions, in order to be incorporated into the IFS_RPM system, after reaching its maturity state.","PeriodicalId":23650,"journal":{"name":"viXra","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"viXra","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21203/rs.3.rs-58308/v1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Forecasting forthcoming "health events" is an extremely challenging task for the Remote Patient Monitoring systems (RPM systems) sector, which relies in real time information and communication technologies. Remote patient monitoring is a medical service which includes following and observing patients that are not in the same location with their health care provider. In general, the patient is equipped with a “smart” monitoring device, and the recorded data (vital signs) are securely transmitted via telecommunication networks to the health care provider. Modern remote patient monitoring devices are small, discrete and easy to wear, allowing "bearers" to move freely and with comfort. In this framework, MOKAAL pc has developed the IFS_RPM service (Integrated Facilitation Services for Remote Patient Monitoring) supplying the necessary ICT infrastructure, which is necessary for the provision of the RPM services. Following the completion of IFS_RPM project, MOKAAL pc launched a research project under the code name "PROPHETTM" . PROPHETTM main objective is to investigate the possibilities of introducing a real time predicting model based on remotely collected vital signs, that would utilize time series of metric data in conjunction with the information stored in the Electronic Health Records (EHR) of the "bearer", attempting to predict in real time, the probability of a "health event" occurring in the near future. To meet this objective, the PROPHETTM project team designed an evolutionary prototype of the "health event" forecasting model, which was developed and tested in a laboratory environment and it will be upgraded to a working prototype to be tested in real conditions, in order to be incorporated into the IFS_RPM system, after reaching its maturity state.
PROPHET项目:初步结果的简要报告
对于依赖实时信息和通信技术的远程患者监测系统(RPM系统)部门来说,预测即将发生的“卫生事件”是一项极具挑战性的任务。远程患者监测是一种医疗服务,包括跟踪和观察与医疗保健提供者不在同一地点的患者。一般来说,患者配备了“智能”监测设备,记录的数据(生命体征)通过电信网络安全地传输给医疗保健提供者。现代远程病人监护设备体积小,分散,易于佩戴,允许“携带者”自由舒适地移动。在此框架下,MOKAAL pc开发了IFS_RPM服务(远程患者监护综合促进服务),提供必要的ICT基础设施,这是提供RPM服务所必需的。随着IFS_RPM项目的完成,MOKAAL pc启动了一个代号为“PROPHETTM”的研究项目。PROPHETTM的主要目标是研究引入基于远程收集的生命体征的实时预测模型的可能性,该模型将利用度量数据的时间序列与存储在“持有者”电子健康记录(EHR)中的信息相结合,试图实时预测近期发生“健康事件”的概率。为了实现这一目标,PROPHETTM项目团队设计了“健康事件”预测模型的进化原型,该模型在实验室环境中开发和测试,并将升级为工作原型,在实际条件下进行测试,以便在达到成熟状态后纳入IFS_RPM系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信