{"title":"创建支持心血管疾病模拟的复杂适应系统模型的方法","authors":"Orlando Simpson, Sergio G. Camorlinga","doi":"10.1109/SYSCON.2015.7116756","DOIUrl":null,"url":null,"abstract":"This paper describes a methodology for creating a Complex Adaptive System (CAS) computer model that supports assessments of Cardiovascular Diseases (CVD) over a period of time. The Agent Based Model (ABM) was implemented in NetLogo and allowed for the complex interdependency of the risk factors and feedback loops from the health interventions at different levels. The CVD assessments are normally based on mathematical equations, predictive risk algorithms or the World Health Organization/International Society of Hypertension (WHO/ISH) predication charts. The 10 year WHO/ISH risk score charts are particularly important because they are calibrated for low and middle income countries unlike the popular Framingham Risk Score and the Systematic Coronary Risk Evaluation (SCORE). WHO/ISH charts contain risk factors that are easier to maintain as a part of medical records of persons in low and middle income countries. The Framingham Risk Score and SCORE were developed and validated in high income countries predominantly with Caucasian populations. Steps to create the model based on WHO/ISH prediction charts are described. The model is applicable to low and middle income countries which account for 80% of CVD related deaths globally.","PeriodicalId":251318,"journal":{"name":"2015 Annual IEEE Systems Conference (SysCon) Proceedings","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A methodology to create Complex Adaptive System models that support Cardiovascular Diseases simulation\",\"authors\":\"Orlando Simpson, Sergio G. Camorlinga\",\"doi\":\"10.1109/SYSCON.2015.7116756\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a methodology for creating a Complex Adaptive System (CAS) computer model that supports assessments of Cardiovascular Diseases (CVD) over a period of time. The Agent Based Model (ABM) was implemented in NetLogo and allowed for the complex interdependency of the risk factors and feedback loops from the health interventions at different levels. The CVD assessments are normally based on mathematical equations, predictive risk algorithms or the World Health Organization/International Society of Hypertension (WHO/ISH) predication charts. The 10 year WHO/ISH risk score charts are particularly important because they are calibrated for low and middle income countries unlike the popular Framingham Risk Score and the Systematic Coronary Risk Evaluation (SCORE). WHO/ISH charts contain risk factors that are easier to maintain as a part of medical records of persons in low and middle income countries. The Framingham Risk Score and SCORE were developed and validated in high income countries predominantly with Caucasian populations. Steps to create the model based on WHO/ISH prediction charts are described. The model is applicable to low and middle income countries which account for 80% of CVD related deaths globally.\",\"PeriodicalId\":251318,\"journal\":{\"name\":\"2015 Annual IEEE Systems Conference (SysCon) Proceedings\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Annual IEEE Systems Conference (SysCon) Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SYSCON.2015.7116756\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Annual IEEE Systems Conference (SysCon) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYSCON.2015.7116756","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A methodology to create Complex Adaptive System models that support Cardiovascular Diseases simulation
This paper describes a methodology for creating a Complex Adaptive System (CAS) computer model that supports assessments of Cardiovascular Diseases (CVD) over a period of time. The Agent Based Model (ABM) was implemented in NetLogo and allowed for the complex interdependency of the risk factors and feedback loops from the health interventions at different levels. The CVD assessments are normally based on mathematical equations, predictive risk algorithms or the World Health Organization/International Society of Hypertension (WHO/ISH) predication charts. The 10 year WHO/ISH risk score charts are particularly important because they are calibrated for low and middle income countries unlike the popular Framingham Risk Score and the Systematic Coronary Risk Evaluation (SCORE). WHO/ISH charts contain risk factors that are easier to maintain as a part of medical records of persons in low and middle income countries. The Framingham Risk Score and SCORE were developed and validated in high income countries predominantly with Caucasian populations. Steps to create the model based on WHO/ISH prediction charts are described. The model is applicable to low and middle income countries which account for 80% of CVD related deaths globally.