Arkadiusz Dziedzic, Julien Issa, Akhilanand Chaurasia, Marta Tanasiewicz
{"title":"人工智能与健康相关数据:患者最佳利益与数据所有权的两难选择","authors":"Arkadiusz Dziedzic, Julien Issa, Akhilanand Chaurasia, Marta Tanasiewicz","doi":"10.1177/09544119241279630","DOIUrl":null,"url":null,"abstract":"The rapid advancement of artificial intelligence (AI) in healthcare has the potential to revolutionize the global healthcare sector and medicine in general. However, integrating AI technologies in healthcare requires access to large amounts of personal health-related data (HRD), which raises concerns regarding confidential personal information considering unregulated and not transparent data ownership. Setting up the patient’s welfare as an unquestionable principle, this commentary explores the various ethical aspects of using HRD in AI applications, focusing on informed consent, data ownership, data sharing, financial considerations, accountability, and ethical standards. Three models of potential collaboration between AI-specializing firms and healthcare providers are evaluated: the commercial model, the equitable profit-sharing model, and the public-funded non-profit model. Each model has its advantages and challenges, necessitating a careful balance between ethical considerations, financial implications, and technological advancements. Policymakers and healthcare regulators are urged to establish transparent legislation to safeguard patient privacy, ensure informed consent, and promote the responsible use of HRD in AI applications. This commentary emphasizes the importance of addressing ethical issues to protect basic patient rights, foster responsible collaborations, and ensure the ethical use of health-related data in AI-based healthcare applications. While the coexistence of regulated AI and healthcare professionals is inevitable for validating the cost-effectiveness of AI use in healthcare economics, the transparency of HRD sources is deemed of utmost importance in the best interest of the patient.","PeriodicalId":20666,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence and health-related data: The patient’s best interest and data ownership dilemma\",\"authors\":\"Arkadiusz Dziedzic, Julien Issa, Akhilanand Chaurasia, Marta Tanasiewicz\",\"doi\":\"10.1177/09544119241279630\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid advancement of artificial intelligence (AI) in healthcare has the potential to revolutionize the global healthcare sector and medicine in general. However, integrating AI technologies in healthcare requires access to large amounts of personal health-related data (HRD), which raises concerns regarding confidential personal information considering unregulated and not transparent data ownership. Setting up the patient’s welfare as an unquestionable principle, this commentary explores the various ethical aspects of using HRD in AI applications, focusing on informed consent, data ownership, data sharing, financial considerations, accountability, and ethical standards. Three models of potential collaboration between AI-specializing firms and healthcare providers are evaluated: the commercial model, the equitable profit-sharing model, and the public-funded non-profit model. Each model has its advantages and challenges, necessitating a careful balance between ethical considerations, financial implications, and technological advancements. Policymakers and healthcare regulators are urged to establish transparent legislation to safeguard patient privacy, ensure informed consent, and promote the responsible use of HRD in AI applications. This commentary emphasizes the importance of addressing ethical issues to protect basic patient rights, foster responsible collaborations, and ensure the ethical use of health-related data in AI-based healthcare applications. 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Artificial intelligence and health-related data: The patient’s best interest and data ownership dilemma
The rapid advancement of artificial intelligence (AI) in healthcare has the potential to revolutionize the global healthcare sector and medicine in general. However, integrating AI technologies in healthcare requires access to large amounts of personal health-related data (HRD), which raises concerns regarding confidential personal information considering unregulated and not transparent data ownership. Setting up the patient’s welfare as an unquestionable principle, this commentary explores the various ethical aspects of using HRD in AI applications, focusing on informed consent, data ownership, data sharing, financial considerations, accountability, and ethical standards. Three models of potential collaboration between AI-specializing firms and healthcare providers are evaluated: the commercial model, the equitable profit-sharing model, and the public-funded non-profit model. Each model has its advantages and challenges, necessitating a careful balance between ethical considerations, financial implications, and technological advancements. Policymakers and healthcare regulators are urged to establish transparent legislation to safeguard patient privacy, ensure informed consent, and promote the responsible use of HRD in AI applications. This commentary emphasizes the importance of addressing ethical issues to protect basic patient rights, foster responsible collaborations, and ensure the ethical use of health-related data in AI-based healthcare applications. While the coexistence of regulated AI and healthcare professionals is inevitable for validating the cost-effectiveness of AI use in healthcare economics, the transparency of HRD sources is deemed of utmost importance in the best interest of the patient.
期刊介绍:
The Journal of Engineering in Medicine is an interdisciplinary journal encompassing all aspects of engineering in medicine. The Journal is a vital tool for maintaining an understanding of the newest techniques and research in medical engineering.