Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(5), P. 1605 - 1605
Published: Feb. 27, 2025
Background/Objectives: Artificial intelligence (AI) is transforming healthcare, enabling advances in diagnostics, treatment optimization, and patient care. Yet, its integration raises ethical, regulatory, societal challenges. Key concerns include data privacy risks, algorithmic bias, regulatory gaps that struggle to keep pace with AI advancements. This study aims synthesize a multidisciplinary framework for trustworthy focusing on transparency, accountability, fairness, sustainability, global collaboration. It moves beyond high-level ethical discussions provide actionable strategies implementing clinical contexts. Methods: A structured literature review was conducted using PubMed, Scopus, Web of Science. Studies were selected based relevance ethics, governance, policy prioritizing peer-reviewed articles, analyses, case studies, guidelines from authoritative sources published within the last decade. The conceptual approach integrates perspectives clinicians, ethicists, policymakers, technologists, offering holistic “ecosystem” view AI. No trials or patient-level interventions conducted. Results: analysis identifies key current governance introduces Regulatory Genome—an adaptive oversight aligned trends Sustainable Development Goals. quantifiable trustworthiness metrics, comparative categories applications, bias mitigation strategies. Additionally, it presents interdisciplinary recommendations aligning deployment environmental sustainability goals. emphasizes measurable standards, multi-stakeholder engagement strategies, partnerships ensure future innovations meet practical healthcare needs. Conclusions: Trustworthy requires more than technical advancements—it demands robust safeguards, proactive regulation, continuous By adopting recommended roadmap, stakeholders can foster responsible innovation, improve outcomes, maintain public trust AI-driven healthcare.
Language: Английский