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人工智能与放射技师的初步影像评估:在急性情况下提供X光解读的放射技师的未来会是怎样?

Artificial intelligence and radiographer preliminary image evaluation: What might the future hold for radiographers providing x-ray interpretation in the acute setting?

作者信息

Rainey Clare

机构信息

School of Health Sciences, Ulster University, Belfast, UK.

出版信息

J Med Radiat Sci. 2024 Dec;71(4):495-498. doi: 10.1002/jmrs.821. Epub 2024 Sep 20.

Abstract

In a stretched healthcare system, radiographer preliminary image evaluation in the acute setting can be a means to optimise patient care by reducing error and increasing efficiencies in the patient journey. Radiographers have shown impressive accuracies in the provision of these initial evaluations, however, barriers such as a lack of confidence and increased workloads have been cited as a reason for radiographer reticence in engagement with this practice. With advances in Artificial Intelligence (AI) technology for assistance in clinical decision-making, and indication that this may increase confidence in diagnostic decision-making with reporting radiographers, the author of this editorial wonders what the impact of this technology might be on clinical decision-making by radiographers in the provision of Preliminary Image Evaluation (PIE).

摘要

在一个不堪重负的医疗体系中,放射技师在急症情况下进行初步影像评估,可成为一种优化患者护理的手段,即减少差错并提高患者就医流程的效率。放射技师在提供这些初始评估方面已展现出令人瞩目的准确性,然而,诸如缺乏信心和工作量增加等障碍,已被视为放射技师不愿参与此项工作的原因。随着人工智能(AI)技术在临床决策辅助方面的进展,并且有迹象表明这可能会增强影像报告技师在诊断决策中的信心,这篇社论的作者想知道这项技术对放射技师在进行初步影像评估(PIE)时的临床决策可能会产生什么影响。

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