Artificial Intelligence in Radiology: Opportunities and Challenges

IF 1.5 4区医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Seminars in Ultrasound Ct and Mri Pub Date : 2024-04-01 DOI:10.1053/j.sult.2024.02.004

Marta N. Flory MD (Clinical Assistant Professor), Sandy Napel PhD (Professor of Radiology and, by courtesy, of Medicine (Informatics) and Electrical Engineering), Emily B. Tsai MD (Clinical Associate Professor)

引用次数: 0

Abstract

Artificial intelligence’s (AI) emergence in radiology elicits both excitement and uncertainty. AI holds promise for improving radiology with regards to clinical practice, education, and research opportunities. Yet, AI systems are trained on select datasets that can contain bias and inaccuracies. Radiologists must understand these limitations and engage with AI developers at every step of the process – from algorithm initiation and design to development and implementation – to maximize benefit and minimize harm that can be enabled by this technology.

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放射学中的人工智能：机遇与挑战。

人工智能（AI）在放射学领域的出现既令人兴奋，又充满不确定性。人工智能有望改善放射学的临床实践、教育和研究机会。然而，人工智能系统是在选定的数据集上进行训练的，可能存在偏差和误差。放射科医生必须了解这些局限性，并在从算法启动和设计到开发和实施的每一步都与人工智能开发人员合作，以最大限度地提高这项技术的效益，减少其危害。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Seminars in Ultrasound Ct and Mri 医学-核医学

CiteScore

2.60

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： Seminars in Ultrasound, CT and MRI is directed to all physicians involved in the performance and interpretation of ultrasound, computed tomography, and magnetic resonance imaging procedures. It is a timely source for the publication of new concepts and research findings directly applicable to day-to-day clinical practice. The articles describe the performance of various procedures together with the authors'' approach to problems of interpretation.