The Governance of Artificial Intelligence in Healthcare: Ethical Foundations, Legal Challenges, and Implementation Realities.
Artificial intelligence (AI) is transforming healthcare across diagnostics, decision-making, and clinical workflows, yet its integration raises complex ethical, legal, and operational challenges. This narrative review synthesizes three traditionally fragmented domains: Ethical principles, legal acco...
| Publicado en: | Lokman Hekim Health Sciences Vol. 6; no. 2; pp. 372 - 383 |
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| Autor principal: | |
| Formato: | review tables/charts Journal Article |
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KARE Publishing
Jun2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194639963&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 194639963 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 27917835 N1MV jtl: Lokman Hekim Health Sciences issn: 27917835 maglogo: N pubinfo: dt: Jun2026 vid: 6 iid: 2 pid: 62027 pub: KARE Publishing artinfo: ui: 194639963 194639963 194639963 10.14744/lhhs.2026.37118 194639963 ppf: 372 ppct: 11 formats: fmt: @attributes: type: P tig: atl: The Governance of Artificial Intelligence in Healthcare: Ethical Foundations, Legal Challenges, and Implementation Realities. aug: au: Yılmaz, Mahmut affil: Department of Intensive Care, İzmir City Hospital, İzmir, Türkiye sug: subj: Artificial Intelligence Legislation and Jurisprudence Artificial Intelligence Ethical Issues Clinical Governance Health Care Delivery Implementation Science Health Care Reform Liability, Legal Medical Informatics Privacy and Confidentiality Rules and Regulations Health Policy Data Security Accountability Decision Making, Ethical Organizational Objectives Organizational Policies Turkiye Organizational Efficiency Diagnosis, Computer Assisted Workflow ab: Artificial intelligence (AI) is transforming healthcare across diagnostics, decision-making, and clinical workflows, yet its integration raises complex ethical, legal, and operational challenges. This narrative review synthesizes three traditionally fragmented domains: Ethical principles, legal accountability, and implementation realities. We draw on literature from major databases alongside regulatory frameworks, including the World Health Organization, the Organisation for Economic Co-operation and Development, the National Institute of Standards and Technology, the European Union (EU), the Food and Drug Administration (FDA), and the International Medical Device Regulators Forum, and examine Türkiye's policies (e.g., Personal Data Protection Law No. 6698) to provide a middle-income country perspective. This review makes three contributions. First, we reconceptualize core bioethical principles - autonomy, beneficence, non-maleficence, and justice - in AI-mediated settings, emphasizing transparency, human oversight, and equity-sensitive design. Second, we frame legal accountability as a distributed system involving developers, institutions, and clinicians. Third, we bridge theory and practice through real-world cases (sepsis prediction vs. proprietary algorithms) and propose an integrated lifecycle governance model. Comparative analysis of the EU AI Act, FDA's 2026 guidance, and Türkiye's regulatory landscape shows convergence toward risk-based governance, alongside persistent gaps, particularly in middle-income settings. Responsible AI governance requires not only regulatory compliance but also continuous evaluation, transparency, and human-centered oversight. Despite global convergence on high-level principles, significant gaps remain in translating these into enforceable mechanisms and clinical practice. Future research should prioritize empirically validated governance models that ensure AI augments - rather than undermines - clinical judgment and patient trust. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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