Teacher of International School of Finance Technology and Science institute

Abstract

Artificial intelligence (AI) is increasingly integrated into healthcare systems for medical imaging, disease prediction, clinical decision support, patient monitoring, administrative management and, more recently, generative clinical applications. The rapid adoption of AI creates significant opportunities for improving accessibility, diagnostic accuracy and health-system efficiency, but it simultaneously challenges legal frameworks traditionally designed around identifiable human decision-makers and relatively static medical technologies. Questions concerning patient autonomy, health-data protection, algorithmic discrimination, transparency, clinical validation, professional liability and post-market monitoring have consequently become central to contemporary health law. This article examines the emerging international and comparative legal framework governing artificial intelligence in healthcare and assesses its implications for Uzbekistan. The research applies doctrinal, comparative and normative legal methods to analyse the World Health Organization's regulatory and ethical standards, the UNESCO Recommendation on the Ethics of Artificial Intelligence, the Council of Europe Framework Convention on Artificial Intelligence, the European Union Artificial Intelligence Act, recent scholarship on medical AI liability, and Uzbekistan's evolving legislation and national AI strategy. The article argues that general AI regulation alone is insufficient for clinical applications because healthcare AI creates distinctive risks to life, health, privacy and equality. Although Uzbekistan has adopted a national strategy for artificial intelligence development until 2030 and has identified healthcare as a priority field for AI deployment, a sector-specific regulatory architecture for medical AI remains necessary. The article proposes a risk-based model comprising six interconnected elements: classification of healthcare AI according to clinical risk; mandatory pre-market clinical and algorithmic validation; strengthened governance of health data; meaningful human oversight; a distributed liability framework; combined with regulatory adaptation to Uzbekistan's healthcare and digital infrastructure, could allow the country to promote innovation without weakening patient protection. and continuous post-deployment monitoring. It concludes that alignment with emerging international standards,