{"title":"压力相关疾病风险的数学建模:综述","authors":"Andrej S. Terehov, M. Yakovlev","doi":"10.38025/2078-1962-2023-22-4-159-166","DOIUrl":null,"url":null,"abstract":"INTRODUCTION. Stress is one of the risk factors for chronic non-communicable diseases, such as cardiovascular diseases, autoimmune disorders, mental disorders, and neurotic conditions like depression and anxiety. Therefore, it is important to predict and correct stress-related problems early. AIM. To assess the impact of stress on the human body, a comprehensive review of both Russian and international sources was conducted across databases like PubMed, eLibrary, and CyberLeninka for the period 2011–2023. The search terms used included “stress effect”, “predictive model”, “mathematical modeling”, “stress”, “mathematical model”, and “stress-related diseases”. CONCLUSION. The literature review has revealed that chronic stress exerts a significant negative impact on the human body, verifiably leading to disorders of the digestive, nervous, endocrine, cardiovascular, and immune systems. At the current stage, stress diagnosis is conducted using both questionnaire methods and instrumental techniques, each having its respective advantages and limitations. Several scientific studies emphasize the importance of mathematical modeling as a tool for simulating the effects of stress on the body and analyzing the key mechanisms predisposing to the development of pathologies. The algorithms for constructing predictive models presented in this publication may serve as a foundation for the development of an automated expert advisory system.","PeriodicalId":397121,"journal":{"name":"Bulletin of Rehabilitation Medicine","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mathematical Modeling of the Risks of Stress-Related Diseases: a Review\",\"authors\":\"Andrej S. Terehov, M. Yakovlev\",\"doi\":\"10.38025/2078-1962-2023-22-4-159-166\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"INTRODUCTION. Stress is one of the risk factors for chronic non-communicable diseases, such as cardiovascular diseases, autoimmune disorders, mental disorders, and neurotic conditions like depression and anxiety. Therefore, it is important to predict and correct stress-related problems early. AIM. To assess the impact of stress on the human body, a comprehensive review of both Russian and international sources was conducted across databases like PubMed, eLibrary, and CyberLeninka for the period 2011–2023. The search terms used included “stress effect”, “predictive model”, “mathematical modeling”, “stress”, “mathematical model”, and “stress-related diseases”. CONCLUSION. The literature review has revealed that chronic stress exerts a significant negative impact on the human body, verifiably leading to disorders of the digestive, nervous, endocrine, cardiovascular, and immune systems. At the current stage, stress diagnosis is conducted using both questionnaire methods and instrumental techniques, each having its respective advantages and limitations. Several scientific studies emphasize the importance of mathematical modeling as a tool for simulating the effects of stress on the body and analyzing the key mechanisms predisposing to the development of pathologies. The algorithms for constructing predictive models presented in this publication may serve as a foundation for the development of an automated expert advisory system.\",\"PeriodicalId\":397121,\"journal\":{\"name\":\"Bulletin of Rehabilitation Medicine\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bulletin of Rehabilitation Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.38025/2078-1962-2023-22-4-159-166\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of Rehabilitation Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.38025/2078-1962-2023-22-4-159-166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mathematical Modeling of the Risks of Stress-Related Diseases: a Review
INTRODUCTION. Stress is one of the risk factors for chronic non-communicable diseases, such as cardiovascular diseases, autoimmune disorders, mental disorders, and neurotic conditions like depression and anxiety. Therefore, it is important to predict and correct stress-related problems early. AIM. To assess the impact of stress on the human body, a comprehensive review of both Russian and international sources was conducted across databases like PubMed, eLibrary, and CyberLeninka for the period 2011–2023. The search terms used included “stress effect”, “predictive model”, “mathematical modeling”, “stress”, “mathematical model”, and “stress-related diseases”. CONCLUSION. The literature review has revealed that chronic stress exerts a significant negative impact on the human body, verifiably leading to disorders of the digestive, nervous, endocrine, cardiovascular, and immune systems. At the current stage, stress diagnosis is conducted using both questionnaire methods and instrumental techniques, each having its respective advantages and limitations. Several scientific studies emphasize the importance of mathematical modeling as a tool for simulating the effects of stress on the body and analyzing the key mechanisms predisposing to the development of pathologies. The algorithms for constructing predictive models presented in this publication may serve as a foundation for the development of an automated expert advisory system.