Johns Hopkins University School of Medicine, 600 N. Wolfe Street / Phipps 446, Baltimore, MD 21287, USA.
Johns Hopkins University School of Medicine, 600 N. Wolfe Street / Phipps 446, Baltimore, MD 21287, USA.
Radiol Clin North Am. 2024 Nov;62(6):935-947. doi: 10.1016/j.rcl.2024.03.008. Epub 2024 Apr 24.
The integration of artificial intelligence (AI) in radiology has brought about substantial advancements and transformative potential in diagnostic imaging practices. This study presents an overview of the current research on the application of AI in radiology, highlighting key insights from recent studies and surveys. These recent studies have explored the expected impact of AI, encompassing machine learning and deep learning, on the work volume of diagnostic radiologists. The present and future role of AI in radiology holds great promise for enhancing diagnostic capabilities, improving workflow efficiency, and ultimately, advancing patient care.
人工智能（AI）在放射学中的整合，为诊断成像实践带来了实质性的进步和变革潜力。本研究概述了目前 AI 在放射学中的应用研究，重点介绍了最近的研究和调查中的关键见解。这些最近的研究探讨了 AI 的预期影响，包括机器学习和深度学习，对诊断放射科医生工作量的影响。目前和未来 AI 在放射学中的作用有望增强诊断能力、提高工作流程效率，并最终改善患者护理。
