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）方法通过提升医学专家和患者的体验，具有变革众多医疗领域的巨大潜力。若基于AI的计算机辅助诊断工具能够超越或达到临床专家水平，将带来巨大益处。由此，发展中国家可负担先进的医疗服务，且专业医疗从业者匮乏的问题可得到缓解。基于AI的工具能够节省患者治疗的时间、资源和总体成本。此外，与人类相比，AI能从大量输入数据中发现复杂关联，甚至推动医学领域产生新的循证知识。然而，将AI整合至医疗保健领域会引发偏见、透明度、自主性、责任与问责等伦理及哲学问题，这些问题需在将此类工具应用于临床环境前加以解决。本文重点阐述了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。我们涵盖了AI的技术与伦理挑战，以及AI在医院及公共机构部署的影响。我们还讨论了应对伦理挑战、数据稀缺、种族偏见、缺乏透明度及算法偏见等问题的关键措施与技术。最后，我们为应对AI在医疗应用中的伦理挑战提出了建议与未来方向，目标是将AI部署至临床环境，为全球患者提供更高效、精准、可及、透明且可靠的工作流程。