Artificial intelligence (AI) methods have great potential to revolutionize numerous medical care by enhancing the experience of medical experts and patients. AI based computer-assisted diagnosis tools can have a tremendous benefit if they can outperform or perform similarly to the level of a clinical expert. As a result, advanced healthcare services can be affordable in developing nations, and the problem of a lack of expert medical practitioners can be addressed. AI based tools can save time, resources, and overall cost for patient treatment. Furthermore, in contrast to humans, AI can uncover complex relations in the data from a large set of inputs and even lead to new evidence-based knowledge in medicine. However, integrating AI in healthcare raises several ethical and philosophical concerns, such as bias, transparency, autonomy, responsibility and accountability, which must be addressed before integrating such tools into clinical settings. In this article, we emphasize recent advances in AI-assisted medical image analysis, existing standards, and the significance of comprehending ethical issues and best practices for the applications of AI in clinical settings. We cover the technical and ethical challenges of AI and the implications of deploying AI in hospitals and public organizations. We also discuss promising key measures and techniques to address the ethical challenges, data scarcity, racial bias, lack of transparency, and algorithmic bias. Finally, we provide our recommendation and future directions for addressing the ethical challenges associated with AI in healthcare applications, with the goal of deploying AI into the clinical settings to make the workflow more efficient, accurate, accessible, transparent, and reliable for the patient worldwide.

翻译：人工智能（AI）方法通过增强医学专家和患者的体验，具有彻底革新众多医疗领域的巨大潜力。基于AI的计算机辅助诊断工具若能超越或达到临床专家水平，将带来显著效益。由此，发展中国家可负担先进医疗服务，同时缓解专业医疗从业者短缺的问题。AI工具能节省患者治疗的时间、资源和总体成本。此外，与人类相比，AI能从大规模输入数据中揭示复杂关联，甚至为医学带来基于证据的新知识。然而，将AI融入医疗领域会引发诸多伦理与哲学考量，如偏见、透明度、自主性、责任与问责，这些必须在将该类工具应用于临床环境前加以解决。本文着重探讨AI辅助医学图像分析的最新进展、现有标准，以及理解伦理问题与临床AI应用最佳实践的重要性。我们涵盖AI的技术与伦理挑战，以及在医院与公共机构部署AI的潜在影响。同时讨论应对伦理挑战、数据稀缺、种族偏见、透明度缺失及算法偏见的关键措施与技术。最后，我们提出关于解决医疗AI应用中伦理挑战的建议与未来方向，目标是将AI部署至临床环境，使其为全球患者的工作流程更高效、精准、可及、透明且可靠。