NYU Langone Health, New York, NY.
J Thorac Imaging. 2020 May;35(3):137-142. doi: 10.1097/RTI.0000000000000486.
Artificial intelligence (AI) is a broad field of computational science that includes many subsets. Today the most widely used subset in medical imaging is machine learning (ML). Many articles have focused on the use of ML for pattern recognition to detect and potentially diagnose various pathologies. However, AI algorithm development is now directed toward workflow management. AI can impact patient care at multiple stages of their imaging experience and assist in efficient and effective scheduling, imaging performance, worklist prioritization, image interpretation, and quality assurance. The purpose of this manuscript was to review the potential AI applications in radiology focusing on workflow management and discuss how ML will affect cardiothoracic imaging.
人工智能（AI）是一个包含许多子领域的广泛的计算科学领域。目前，在医学成像领域应用最广泛的子领域是机器学习（ML）。许多文章都集中在使用 ML 进行模式识别，以检测和潜在诊断各种病理学。然而，人工智能算法的开发现在正朝着工作流程管理的方向发展。人工智能可以在患者的影像学检查体验的多个阶段影响患者的护理，并有助于实现高效和有效的调度、影像学性能、工作列表优先级排序、图像解释和质量保证。本文的目的是回顾人工智能在放射学中的潜在应用，重点是工作流程管理，并讨论机器学习将如何影响心胸影像学。
