{"title":"CARDIOVASCULAR RISK KNOWLEDGE BASE FOR ASSESSMENT AND FORECAST OF STATES","authors":"M. Petryaeva, C. Processes, E. Shalfeeva","doi":"10.22250/isu.2021.69.112-125","DOIUrl":null,"url":null,"abstract":"As part of the process of informatization of health care for the prevention of cardiovascular diseases, it is advisable to create software services to support a doctor in the process of identification and assess-ment of cardiovascular risk factors that can be integrated with the system of electronic medical rec-ords. Such services provide support based on formalized knowledge. A knowledge base of various scales and models for determining and assessing cardiovascular risks has been created. It includes the description of the main predictive scales and models widely used in Russia and abroad, as well as new models of higher predictive accuracy.","PeriodicalId":426728,"journal":{"name":"Informatika i sistemy upravleniya","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Informatika i sistemy upravleniya","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22250/isu.2021.69.112-125","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
As part of the process of informatization of health care for the prevention of cardiovascular diseases, it is advisable to create software services to support a doctor in the process of identification and assess-ment of cardiovascular risk factors that can be integrated with the system of electronic medical rec-ords. Such services provide support based on formalized knowledge. A knowledge base of various scales and models for determining and assessing cardiovascular risks has been created. It includes the description of the main predictive scales and models widely used in Russia and abroad, as well as new models of higher predictive accuracy.