Artificial intelligence (AI) methods hold immense potential to revolutionize numerous medical care by enhancing the experience of medical experts and patients. AI-based computer-assisted diagnosis and treatment tools can democratize healthcare by matching the clinical level or surpassing clinical experts. As a result, advanced healthcare services can be affordable to all populations, irrespective of demographics, race, or socioeconomic background. The democratization of such AI tools can reduce the cost of care, optimize resource allocation, and improve the quality of care. 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 into healthcare raises several ethical and philosophical concerns, such as bias, transparency, autonomy, responsibility, and accountability. Here, we emphasize recent advances in AI-assisted medical image analysis, existing standards, and the significance of comprehending ethical issues and best practices for clinical settings. We cover the technical and ethical challenges and implications of deploying AI in hospitals and public organizations. We also discuss key measures and techniques to address ethical challenges, data scarcity, racial bias, lack of transparency, and algorithmic bias and provide recommendations and future directions.

翻译：人工智能方法通过提升医学专家和患者的体验，有望彻底变革众多医疗领域。基于人工智能的计算机辅助诊断与治疗工具能够匹配甚至超越临床专家的水平，从而推动医疗保健的普及化。由此，无论人口特征、种族或社会经济背景如何，所有人群都能负担得起先进的医疗服务。这类人工智能工具的普及能够降低医疗成本、优化资源配置并提升诊疗质量。与人类相比，人工智能能从海量输入数据中揭示复杂关联，甚至催生医学领域新的循证知识。然而，将人工智能整合到医疗体系中会引发诸多伦理与哲学问题，例如偏见、透明度、自主性、责任归属与问责机制。本文聚焦于人工智能辅助医学图像分析的最新进展、现有标准，以及理解临床环境中伦理问题与最佳实践的重要性。我们探讨了在医院和公共机构部署人工智能时面临的技术与伦理挑战及其影响，还讨论了应对伦理困境、数据稀缺、种族偏见、透明度不足及算法偏见的关键措施与技术，并提出了相关建议与未来方向。