L. Yasnitsky, A. Dumler, F. Cherepanov, V. L. Yasnitsky, Natalia A. Uteva
{"title":"神经网络技术在提取新医学知识和提高患者精确决策方面的能力","authors":"L. Yasnitsky, A. Dumler, F. Cherepanov, V. L. Yasnitsky, Natalia A. Uteva","doi":"10.1080/23808993.2021.1993595","DOIUrl":null,"url":null,"abstract":"ABSTRACT Objectives Currently, there is an active use of neural networks in various areas of human activity. Problems of recognition, diagnostics, optimization, forecasting, control, as well as obtaining new scientific knowledge are successfully solved. However, in medicine, due to the particular complexity of the human body, neural networks are mainly used only for solving the simplest problems of classification and diagnostics. The purpose of this article is to show that the possibilities of neural network modeling in medicine are much wider. Methods This goal is achieved by using special mathematical techniques developed by the authors that allow us to overcome these difficulties. Results The intellectual system created in this way made it possible to reveal a number of interesting scientific knowledge, which sometimes does not coincide with the generally accepted ideas of doctors. Virtual experiments conducted on computer models of patients using our intelligent system clearly demonstrate which lifestyle and medication variations can benefit a particular patient in the long term, and which can cause harm. Conclusion Our intellectual system allows us to identify new scientific knowledge, to carry out long-term forecasting of the development of the disease, to select the optimal courses of treatment and prevention of diseases.","PeriodicalId":12124,"journal":{"name":"Expert Review of Precision Medicine and Drug Development","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Capabilities of neural network technologies for extracting new medical knowledge and enhancing precise decision making for patients\",\"authors\":\"L. Yasnitsky, A. Dumler, F. Cherepanov, V. L. Yasnitsky, Natalia A. Uteva\",\"doi\":\"10.1080/23808993.2021.1993595\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Objectives Currently, there is an active use of neural networks in various areas of human activity. Problems of recognition, diagnostics, optimization, forecasting, control, as well as obtaining new scientific knowledge are successfully solved. However, in medicine, due to the particular complexity of the human body, neural networks are mainly used only for solving the simplest problems of classification and diagnostics. The purpose of this article is to show that the possibilities of neural network modeling in medicine are much wider. Methods This goal is achieved by using special mathematical techniques developed by the authors that allow us to overcome these difficulties. Results The intellectual system created in this way made it possible to reveal a number of interesting scientific knowledge, which sometimes does not coincide with the generally accepted ideas of doctors. Virtual experiments conducted on computer models of patients using our intelligent system clearly demonstrate which lifestyle and medication variations can benefit a particular patient in the long term, and which can cause harm. Conclusion Our intellectual system allows us to identify new scientific knowledge, to carry out long-term forecasting of the development of the disease, to select the optimal courses of treatment and prevention of diseases.\",\"PeriodicalId\":12124,\"journal\":{\"name\":\"Expert Review of Precision Medicine and Drug Development\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Expert Review of Precision Medicine and Drug Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/23808993.2021.1993595\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Review of Precision Medicine and Drug Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23808993.2021.1993595","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Capabilities of neural network technologies for extracting new medical knowledge and enhancing precise decision making for patients
ABSTRACT Objectives Currently, there is an active use of neural networks in various areas of human activity. Problems of recognition, diagnostics, optimization, forecasting, control, as well as obtaining new scientific knowledge are successfully solved. However, in medicine, due to the particular complexity of the human body, neural networks are mainly used only for solving the simplest problems of classification and diagnostics. The purpose of this article is to show that the possibilities of neural network modeling in medicine are much wider. Methods This goal is achieved by using special mathematical techniques developed by the authors that allow us to overcome these difficulties. Results The intellectual system created in this way made it possible to reveal a number of interesting scientific knowledge, which sometimes does not coincide with the generally accepted ideas of doctors. Virtual experiments conducted on computer models of patients using our intelligent system clearly demonstrate which lifestyle and medication variations can benefit a particular patient in the long term, and which can cause harm. Conclusion Our intellectual system allows us to identify new scientific knowledge, to carry out long-term forecasting of the development of the disease, to select the optimal courses of treatment and prevention of diseases.
期刊介绍:
Expert Review of Precision Medicine and Drug Development publishes primarily review articles covering the development and clinical application of medicine to be used in a personalized therapy setting; in addition, the journal also publishes original research and commentary-style articles. In an era where medicine is recognizing that a one-size-fits-all approach is not always appropriate, it has become necessary to identify patients responsive to treatments and treat patient populations using a tailored approach. Areas covered include: Development and application of drugs targeted to specific genotypes and populations, as well as advanced diagnostic technologies and significant biomarkers that aid in this. Clinical trials and case studies within personalized therapy and drug development. Screening, prediction and prevention of disease, prediction of adverse events, treatment monitoring, effects of metabolomics and microbiomics on treatment. Secondary population research, genome-wide association studies, disease–gene association studies, personal genome technologies. Ethical and cost–benefit issues, the impact to healthcare and business infrastructure, and regulatory issues.