Shaping the Future of Healthcare: Ethical Clinical Challenges and Pathways to Trustworthy AI

Journal of Clinical Medicine, Год журнала: 2025, Номер 14(5), С. 1605 - 1605

Опубликована: Фев. 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.

Язык: Английский

eHealth Literacy and Trust in Health Information Sources

Healthcare, Год журнала: 2025, Номер 13(6), С. 616 - 616

Опубликована: Март 12, 2025

Introduction: The spread of health-related information across the internet necessitates an evaluation public eHealth literacy, trust in different health sources, including healthcare providers, and how literacy is related to sources. Methods: 407 individuals participated a web-based survey Tabuk region Saudi Arabia. Univariate analysis was used evaluate relationships between demographic variables, multiple linear regression measure relationship sources after adjustment for factors. Results: average respondents 27.17 out 40. levels were higher among females, younger age groups, those higher-education category, with chronic disease or currently on medication. For 51.9% participants, physicians workers their main source information, while 40% considered source. None study participants perceived as untrustworthy, social media least trusted not but positively associated specialized websites negatively media. Conclusions: findings suggest that tends prefer other primary regardless levels. A level distrust

Язык: Английский

Characterizing users and intention to use online health information resources: a comprehensive study

Informatics in Medicine Unlocked, Год журнала: 2025, Номер unknown, С. 101640 - 101640

Опубликована: Апрель 1, 2025

Язык: Английский