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Letter from the Editor - Post-Treatment Imaging Evaluation of the Head and Neck 编者来信-头颈部治疗后影像学评估
IF 0.4 4区 医学 Q4 Medicine Pub Date : 2023-07-01 DOI: 10.1053/j.ro.2023.05.002
Prachi P. Agarwal
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引用次数: 0
Surgical Implants in the Head and Neck: Normal and Abnormal Imaging Appearances 头颈部外科植入物:正常与异常影像表现
IF 0.4 4区 医学 Q4 Medicine Pub Date : 2023-07-01 DOI: 10.1053/j.ro.2023.01.001
Daniel Ginat
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引用次数: 0
Demystifying Surgical Free Flaps in the Head and Neck 头颈部游离皮瓣的解谜术
IF 0.4 4区 医学 Q4 Medicine Pub Date : 2023-07-01 DOI: 10.1053/j.ro.2023.01.004
Ryan T. Beck MD , Tanya Rath MD , Sonia Gill MD , Joseph Zenga MD , Mohit Agarwal MD
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引用次数: 0
Interpreting the Post-Treatment Orbit: Pearls and Pitfalls 解读治疗后的轨道:珍珠和陷阱
IF 0.4 4区 医学 Q4 Medicine Pub Date : 2023-07-01 DOI: 10.1053/j.ro.2023.01.003
Cameron J. Overfield MD, Alok A. Bhatt MD
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引用次数: 0
Reconstructive Surgeries After Head And Neck Trauma: Imaging Appearances 头颈部创伤后的重建手术:影像学表现
IF 0.4 4区 医学 Q4 Medicine Pub Date : 2023-07-01 DOI: 10.1053/j.ro.2023.04.003
Michael Kwofie , Bruno Policeni
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引用次数: 0
Artificial Intelligence for Cardiothoracic Imaging: Overview of Current and Emerging Applications 心胸成像中的人工智能:当前和新兴应用综述
IF 0.4 4区 医学 Q4 Medicine Pub Date : 2023-04-01 DOI: 10.1053/j.ro.2023.02.001
Bruno Hochhegger MD , Romulo Pasini MD , Alysson Roncally Carvalho MD , Rosana Rodrigues MD , Stephan Altmayer MD , Leonardo Kayat Bittencourt MD , Edson Marchiori MD , Reza Forghani MD, PhD

Artificial intelligence algorithms can learn by assimilating information from large datasets in order to decipher complex associations, identify previously undiscovered pathophysiological states, and construct prediction models. There has been tremendous interest and increased incorporation of artificial intelligence into various industries, including healthcare. As a result, there has been an exponential rise in the number of research articles and industry participants producing models intended for a variety of applications in medical imaging, which can be challenging to navigate for radiologists. In thoracic imaging, multiple applications are being evaluated for chest radiography and computed tomography and include applications for lung nodule evaluation and cancer imaging, quantifying diffuse lung disorders, and cardiac imaging, to name a few. This review aims to provide an overview of current clinical AI models, focusing on the most common clinical applications of AI in cardiothoracic imaging.

人工智能算法可以通过吸收来自大型数据集的信息来进行学习,以破译复杂的关联,识别以前未发现的病理生理状态,并构建预测模型。人们对人工智能产生了极大的兴趣,并越来越多地将其纳入包括医疗保健在内的各个行业。因此,生产用于医学成像各种应用的模型的研究文章和行业参与者的数量呈指数级增长,这对放射科医生来说可能是一个挑战。在胸部成像方面,正在评估胸部放射线摄影和计算机断层摄影的多种应用,包括肺结节评估和癌症成像、量化弥漫性肺部疾病和心脏成像等应用。这篇综述旨在概述当前的临床人工智能模型,重点介绍人工智能在心胸成像中最常见的临床应用。
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引用次数: 0
Case of the Season: Artificial Intelligence in Clinical Practice—Large Vessel Occlusion Triage in Stroke Imaging 本季度案例:临床实践中的人工智能-脑卒中成像中大血管闭塞分诊
IF 0.4 4区 医学 Q4 Medicine Pub Date : 2023-04-01 DOI: 10.1053/j.ro.2023.02.005
Reza Forghani MD, PhD , Rajiv Gupta MD, PhD
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引用次数: 1
Letter From the Editor: Artificial Intelligence and Radiology 编辑来信:人工智能与放射学
IF 0.4 4区 医学 Q4 Medicine Pub Date : 2023-04-01 DOI: 10.1053/j.ro.2023.01.007
Prachi Agarwal
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引用次数: 0
Artificial Intelligence in Radiology: A Private Practice Perspective From a Large Health System in Latin America 放射学中的人工智能:来自拉丁美洲大型卫生系统的私人执业视角
IF 0.4 4区 医学 Q4 Medicine Pub Date : 2023-04-01 DOI: 10.1053/j.ro.2023.01.006
Paulo E.A. Kuriki, Felipe C. Kitamura

In the field of radiology, the use of artificial intelligence (AI) is increasing. Even though healthcare facilities are interested in using this technology, having success with an AI project can be challenging. There is a myriad of AI solutions today, and comparing them can be challenging. Moreover, the implementation process involves alignment with many different areas. In our institution, we have been testing, developing, deploying, and monitoring AI solutions for the last four years. This article intends to share our experience and highlight the most important points to ensure a successful project based on our experience in the setting of a large private practice in Latin America.

在放射学领域,人工智能(AI)的使用正在增加。尽管医疗机构对使用这项技术感兴趣,但在人工智能项目上取得成功可能是一项挑战。今天有无数的人工智能解决方案,比较它们可能很有挑战性。此外,执行过程涉及与许多不同领域保持一致。在过去的四年里,我们一直在测试、开发、部署和监控人工智能解决方案。本文旨在根据我们在拉丁美洲大型私人诊所的经验,分享我们的经验,并强调最重要的一点,以确保项目成功。
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引用次数: 0
Artificial Intelligence in Radiology: Overview of Application Types, Design, and Challenges 放射学中的人工智能:应用类型、设计和挑战概述
IF 0.4 4区 医学 Q4 Medicine Pub Date : 2023-04-01 DOI: 10.1053/j.ro.2023.01.005
Mana Moassefi , Shahriar Faghani , Bardia Khosravi , Pouria Rouzrokh , Bradley J. Erickson
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引用次数: 1
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Seminars in Roentgenology
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