Harishbhai Tilala Mitul, Kumar Chenchala Pradeep, Choppadandi Ashok, Kaur Jagbir, Naguri Savitha, Saoji Rahul, Devaguptapu Bhanu
Software Engineering, Independent Researcher, Trenton, USA.
Software Development, Independent Researcher, Seattle, USA.
Cureus. 2024 Jun 15;16(6):e62443. doi: 10.7759/cureus.62443. eCollection 2024 Jun.
Artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing health care by offering unprecedented opportunities to enhance patient care, optimize clinical workflows, and advance medical research. However, the integration of AI and ML into healthcare systems raises significant ethical considerations that must be carefully addressed to ensure responsible and equitable deployment. This comprehensive review explored the multifaceted ethical considerations surrounding the use of AI and ML in health care, including privacy and data security, algorithmic bias, transparency, clinical validation, and professional responsibility. By critically examining these ethical dimensions, stakeholders can navigate the ethical complexities of AI and ML integration in health care, while safeguarding patient welfare and upholding ethical principles. By embracing ethical best practices and fostering collaboration across interdisciplinary teams, the healthcare community can harness the full potential of AI and ML technologies to usher in a new era of personalized data-driven health care that prioritizes patient well-being and equity.
人工智能（AI）和机器学习（ML）技术正在彻底改变医疗保健行业，为提升患者护理水平、优化临床工作流程以及推进医学研究带来了前所未有的机遇。然而，将人工智能和机器学习整合到医疗系统中引发了重大的伦理考量，必须谨慎加以解决，以确保其负责任且公平地部署。这一全面综述探讨了围绕在医疗保健中使用人工智能和机器学习的多方面伦理考量，包括隐私和数据安全、算法偏差、透明度、临床验证以及专业责任。通过批判性地审视这些伦理维度，利益相关者能够应对人工智能和机器学习整合到医疗保健中的伦理复杂性，同时保障患者福利并坚持伦理原则。通过采用最佳伦理实践并促进跨学科团队之间的合作，医疗保健界能够充分发挥人工智能和机器学习技术的潜力，迎来一个以患者福祉和平等为优先的个性化数据驱动型医疗保健新时代。
