Recognising errors in AI implementation in radiology: A narrative review

IF 3.2 3区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

European Journal of Radiology Pub Date : 2025-07-10 DOI:10.1016/j.ejrad.2025.112311

Nikolaos Stogiannos , Renato Cuocolo , Tugba Akinci D’Antonoli , Daniel Pinto dos Santos , Hugh Harvey , Merel Huisman , Burak Kocak , Elmar Kotter , Karim Lekadir , Susan Cheng Shelmerdine , Kicky G van Leeuwen , Peter van Ooijen , Michail E. Klontzas , Christina Malamateniou

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引用次数: 0

Abstract

The implementation of AI can suffer from a wide variety of failures. These failures can impact the performance of AI algorithms, impede the adoption of AI solutions in clinical practice, lead to workflow delays, or create unnecessary costs. This narrative review aims to comprehensively discuss different reasons for AI failures in Radiology through the analysis of published evidence across three main components of AI implementation: (i) the AI models throughout their lifecycle, (ii) the technical infrastructure, including the hardware and software needed to develop and deploy AI models and (iii) the human factors involved. Ultimately, based on the identified errors, this report aims to propose solutions to optimise the use and adoption of AI in radiology.

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识别人工智能在放射学应用中的错误：叙述性回顾

人工智能的实施可能会遭遇各种各样的失败。这些故障可能会影响人工智能算法的性能，阻碍人工智能解决方案在临床实践中的采用，导致工作流程延迟，或产生不必要的成本。本叙述性综述旨在通过分析人工智能实施的三个主要组成部分的已发表证据，全面讨论放射学中人工智能失败的不同原因：(i)人工智能模型的整个生命周期，（ii）技术基础设施，包括开发和部署人工智能模型所需的硬件和软件，以及（iii）所涉及的人为因素。最终，基于已识别的错误，本报告旨在提出解决方案，以优化人工智能在放射学中的使用和采用。

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

European Journal of Radiology 医学-核医学

CiteScore

6.70

自引率

3.00%

发文量

398

审稿时长

42 days

期刊介绍： European Journal of Radiology is an international journal which aims to communicate to its readers, state-of-the-art information on imaging developments in the form of high quality original research articles and timely reviews on current developments in the field. Its audience includes clinicians at all levels of training including radiology trainees, newly qualified imaging specialists and the experienced radiologist. Its aim is to inform efficient, appropriate and evidence-based imaging practice to the benefit of patients worldwide.