Medicolegal aspects of the use of artificial intelligence in healthcare: challenges, current regulations, and future directions

Artificial intelligence in medicine: An ethical and legal review.

This review addresses the primary ethical principles relevant to AI in medicine - including respect for patient autonomy, beneficence, non-maleficence, and justice - alongside key legal frameworks with respect to liability, data protection, regulatory compliance, and algorithmic transparency.

Legal Regulation of Artificial Intelligence in Healthcare: Challenges, Opportunities, and Ethical Considerations

Artificial Intelligence (AI) has emerged as a transformative technology in the healthcare sector, revolutionizing medical diagnosis, treatment planning, disease prediction, robotic surgery, personalized medicine, and healthcare administration. AI-driven technologies improve clinical efficiency, reduce human error, accelerate drug discovery, and enhance patient outcomes through data-driven decision-making. However, the widespread adoption of AI in healthcare has introduced complex legal, ethical, and regulatory challenges that existing healthcare laws often struggle to address. Issues relating to patient privacy, informed consent, algorithmic transparency, liability for medical errors, data ownership, cybersecurity, bias in AI algorithms, and cross-border data governance have become central concerns in contemporary health law. As AI systems increasingly participate in clinical decision-making, determining accountability among healthcare professionals, software developers, medical institutions, and regulatory authorities becomes legally complex. Several jurisdictions, including the European Union, the United States, India, and the United Kingdom, have introduced regulatory frameworks to ensure the safe, ethical, and responsible deployment of AI-powered healthcare technologies. This paper critically examines the legal regulation of Artificial Intelligence in healthcare through a comparative analysis of international legal frameworks, judicial developments, and ethical principles governing AI-enabled medical systems. It explores the opportunities AI presents for improving healthcare delivery while evaluating the legal challenges surrounding privacy, liability, fairness, transparency, and patient rights. The study concludes by proposing future regulatory reforms aimed at establishing comprehensive, accountable, and human-centric governance frameworks that promote innovation while protecting fundamental rights and ensuring ethical healthcare delivery in the digital era.

Bridging gaps in health artificial intelligence: challenges in MDPI research articles

This study systematically analyzes research trends in health AI over the past six years through a systematic literature review (SLR) and a bibliometric analysis using VOSviewer to highlight dominant research areas, including machine learning for diagnosis, AI-driven hospital management, and predictive analytics.

[Artificial intelligence and healthcare: why is it difficult to move from the research phase to clinical practice?]

Artificial intelligence (AI) is widely regarded as one of the most promising innovations in healthcare, yet its adoption in routine clinical practice remains limited. Only a small proportion of AI applications developed in research settings are successfully integrated into healthcare delivery. Major barriers include poor interoperability with existing health information systems, complex regulatory requirements, limited scientific evidence, and the lack of clear clinical guidelines. Many AI tools have been evaluated through methodologically weak studies, often retrospective and lacking external validation, contributing to skepticism among healthcare professionals. Additional challenges involve healthcare professionals' education and training, algorithm transparency, and the ability of healthcare organizations to effectively incorporate these technologies into clinical workflows. To promote the safe and effective adoption of AI, stronger clinical evidence, structured training programs, and organizational models capable of supporting its implementation are required. Addressing these issues is essential to ensure that AI can deliver meaningful benefits for patients, healthcare professionals, and healthcare systems.

Navigating AI in clinical practice: A practical guide for physicians.

Artificial intelligence is rapidly entering clinical practice, yet many physicians-especially those in solo or small-group settings-lack the guidance and evaluation resources needed to use these tools safely. Because state medical boards regulate physicians rather than AI developers, clinicians remain fully accountable when AI‑assisted care contributes to patient harm. This article outlines the risks posed by opaque algorithms, hallucinated outputs, omissions, and inequitable model performance, while emphasizing that AI should augment-not replace-clinical judgment. Drawing on recent research and the Federation of State Medical Boards' 2024 guidance, the article clarifies professional responsibilities related to competence, documentation, informed consent, privacy, and bias mitigation. A practical toolkit offers actionable steps for evaluating AI tools, establishing verification protocols, monitoring performance, and ensuring transparency with patients. The article concludes that responsible physician engagement is essential to realizing AI's benefits while preserving patient safety, professional accountability, and equitable care.

Ethical Use of Artificial Intelligence in Public Health: Mitigating Risks and Advancing Health Equity.