{"title":"疾病X疫苗生产和供应链:风险评估与人工智能和工业4.0操作的医疗保健系统。","authors":"Petar Radanliev, David De Roure","doi":"10.1007/s12553-022-00722-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The objective of this theoretical paper is to identify conceptual solutions for securing, predicting, and improving vaccine production and supply chains.</p><p><strong>Method: </strong>The case study, action research, and review method is used with secondary data - publicly available open access data.</p><p><strong>Results: </strong>A set of six algorithmic solutions is presented for resolving vaccine production and supply chain bottlenecks. A different set of algorithmic solutions is presented for forecasting risks during a Disease X event. A new conceptual framework is designed to integrate the emerging solutions in vaccine production and supply chains. The framework is constructed to improve the state-of-the-art by intersecting the previously isolated disciplines of edge computing; cyber-risk analytics; healthcare systems, and AI algorithms.</p><p><strong>Conclusion: </strong>For healthcare systems to cope better during a disease X event than during Covid-19, we need multiple highly specific AI algorithms, targeted for solving specific problems. The proposed framework would reduce production and supply chain risk and complexity in a Disease X event.</p>","PeriodicalId":12941,"journal":{"name":"Health and Technology","volume":"13 1","pages":"11-15"},"PeriodicalIF":3.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811889/pdf/","citationCount":"8","resultStr":"{\"title\":\"Disease X vaccine production and supply chains: risk assessing healthcare systems operating with artificial intelligence and industry 4.0.\",\"authors\":\"Petar Radanliev, David De Roure\",\"doi\":\"10.1007/s12553-022-00722-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>The objective of this theoretical paper is to identify conceptual solutions for securing, predicting, and improving vaccine production and supply chains.</p><p><strong>Method: </strong>The case study, action research, and review method is used with secondary data - publicly available open access data.</p><p><strong>Results: </strong>A set of six algorithmic solutions is presented for resolving vaccine production and supply chain bottlenecks. A different set of algorithmic solutions is presented for forecasting risks during a Disease X event. A new conceptual framework is designed to integrate the emerging solutions in vaccine production and supply chains. The framework is constructed to improve the state-of-the-art by intersecting the previously isolated disciplines of edge computing; cyber-risk analytics; healthcare systems, and AI algorithms.</p><p><strong>Conclusion: </strong>For healthcare systems to cope better during a disease X event than during Covid-19, we need multiple highly specific AI algorithms, targeted for solving specific problems. The proposed framework would reduce production and supply chain risk and complexity in a Disease X event.</p>\",\"PeriodicalId\":12941,\"journal\":{\"name\":\"Health and Technology\",\"volume\":\"13 1\",\"pages\":\"11-15\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811889/pdf/\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s12553-022-00722-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICAL INFORMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s12553-022-00722-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
Disease X vaccine production and supply chains: risk assessing healthcare systems operating with artificial intelligence and industry 4.0.
Objective: The objective of this theoretical paper is to identify conceptual solutions for securing, predicting, and improving vaccine production and supply chains.
Method: The case study, action research, and review method is used with secondary data - publicly available open access data.
Results: A set of six algorithmic solutions is presented for resolving vaccine production and supply chain bottlenecks. A different set of algorithmic solutions is presented for forecasting risks during a Disease X event. A new conceptual framework is designed to integrate the emerging solutions in vaccine production and supply chains. The framework is constructed to improve the state-of-the-art by intersecting the previously isolated disciplines of edge computing; cyber-risk analytics; healthcare systems, and AI algorithms.
Conclusion: For healthcare systems to cope better during a disease X event than during Covid-19, we need multiple highly specific AI algorithms, targeted for solving specific problems. The proposed framework would reduce production and supply chain risk and complexity in a Disease X event.
期刊介绍：
Health and Technology is the first truly cross-disciplinary journal on issues related to health technologies addressing all professions relating to health, care and health technology.The journal constitutes an information platform connecting medical technology and informatics with the needs of care, health care professionals and patients. Thus, medical physicists and biomedical/clinical engineers are encouraged to write articles not only for their colleagues, but directed to all other groups of readers as well, and vice versa.By its nature, the journal presents and discusses hot subjects including but not limited to patient safety, patient empowerment, disease surveillance and management, e-health and issues concerning data security, privacy, reliability and management, data mining and knowledge exchange as well as health prevention. The journal also addresses the medical, financial, social, educational and safety aspects of health technologies as well as health technology assessment and management, including issues such security, efficacy, cost in comparison to the benefit, as well as social, legal and ethical implications.This journal is a communicative source for the health work force (physicians, nurses, medical physicists, clinical engineers, biomedical engineers, hospital engineers, etc.), the ministries of health, hospital management, self-employed doctors, health care providers and regulatory agencies, the medical technology industry, patients'' associations, universities (biomedical and clinical engineering, medical physics, medical informatics, biology, medicine and public health as well as health economics programs), research institutes and professional, scientific and technical organizations.Health and Technology is jointly published by Springer and the IUPESM (International Union for Physical and Engineering Sciences in Medicine) in cooperation with the World Health Organization.
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