UC Davis Medical Center, 4860 Y Street, Suite 3100, Sacramento, CA 95817, USA.
Radiol Clin North Am. 2021 Nov;59(6):1053-1062. doi: 10.1016/j.rcl.2021.07.005.
Artificial intelligence (AI) and informatics promise to improve the quality and efficiency of diagnostic radiology but will require substantially more standardization and operational coordination to realize and measure those improvements. As radiology steps into the AI-driven future we should work hard to identify the needs and desires of our customers and develop process controls to ensure we are meeting them. Rather than focusing on easy-to-measure turnaround times as surrogates for quality, AI and informatics can support more comprehensive quality metrics, such as ensuring that reports are accurate, readable, and useful to patients and health care providers.
人工智能（AI）和信息学有望提高诊断放射学的质量和效率，但需要更多的标准化和运营协调来实现和衡量这些改进。随着放射学步入 AI 驱动的未来，我们应该努力确定客户的需求和期望，并制定流程控制措施以确保满足这些需求。人工智能和信息学不应将易于衡量的周转时间作为质量的替代指标，而是可以支持更全面的质量指标，例如确保报告准确、易读且对患者和医疗保健提供者有用。
