Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-City, Osaka, 565-0871, Japan.
Department of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, 466-8550, Japan.
Radiol Med. 2023 Oct;128(10):1236-1249. doi: 10.1007/s11547-023-01691-w. Epub 2023 Aug 28.
Although there is no solid agreement for artificial intelligence (AI), it refers to a computer system with intelligence similar to that of humans. Deep learning appeared in 2006, and more than 10 years have passed since the third AI boom was triggered by improvements in computing power, algorithm development, and the use of big data. In recent years, the application and development of AI technology in the medical field have intensified internationally. There is no doubt that AI will be used in clinical practice to assist in diagnostic imaging in the future. In qualitative diagnosis, it is desirable to develop an explainable AI that at least represents the basis of the diagnostic process. However, it must be kept in mind that AI is a physician-assistant system, and the final decision should be made by the physician while understanding the limitations of AI. The aim of this article is to review the application of AI technology in diagnostic imaging from PubMed database while particularly focusing on diagnostic imaging in thorax such as lesion detection and qualitative diagnosis in order to help radiologists and clinicians to become more familiar with AI in thorax.
虽然人工智能（AI）尚无明确的定义，但它是指一种具有类似于人类智能的计算机系统。深度学习于 2006 年出现，经过十余年的发展，随着计算能力、算法开发和大数据应用的进步，第三次人工智能热潮被引爆。近年来，国际上人工智能技术在医疗领域的应用和发展不断加强。毫无疑问，未来 AI 将用于临床实践，辅助诊断成像。在定性诊断中，理想的是开发一种可解释的 AI，至少能够代表诊断过程的基础。但是，必须牢记，AI 是一种医生辅助系统，医生应该在了解 AI 局限性的同时做出最终决策。本文的目的是从 PubMed 数据库中回顾 AI 技术在诊断成像中的应用，特别关注胸部诊断成像，如病变检测和定性诊断，以帮助放射科医生和临床医生更加熟悉胸部 AI。
