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人工智能颅内出血识别优先软件在术后阶段的假阳性:两例报告

False Positives in Artificial Intelligence Prioritization Software for Intracranial Hemorrhage Identification in the Postoperative Period: A Report of Two Cases.

作者信息

Cardoso Osmay, Adly Marco, Hamade Mohamad, Saigal Khushi, Saigal Gaurav

机构信息

Radiology, University of Miami Miller School of Medicine, Jackson Memorial Hospital, Miami, USA.

Radiology, University of Florida College of Medicine, Gainesville, USA.

出版信息

Cureus. 2023 Aug 27;15(8):e44215. doi: 10.7759/cureus.44215. eCollection 2023 Aug.

Abstract

The implementation of artificial intelligence (AI) in radiology has shown significant promise in the identification of acute intracranial hemorrhages (ICHs). However, it is crucial to recognize that AI systems may produce false-positive results, especially in the postoperative period. Here, we present two cases where AI prioritization software erroneously identified an acute ICH on a postoperative non-contrast CT. These cases highlight the need for a more careful radiology review of AI-flagged images in postoperative patients to avoid further unnecessary imaging and unwarranted concerns from radiologists, clinicians, and patients.

摘要

人工智能(AI)在放射学中的应用已在急性颅内出血(ICH)的识别方面显示出巨大潜力。然而,必须认识到AI系统可能会产生假阳性结果,尤其是在术后阶段。在此,我们介绍两例AI优先级软件在术后非增强CT上错误识别急性ICH的病例。这些病例凸显了对术后患者中AI标记图像进行更仔细的放射学评估的必要性,以避免进一步不必要的影像学检查以及放射科医生、临床医生和患者无端的担忧。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43b9/10460624/9ccf87e0bcf5/cureus-0015-00000044215-i01.jpg

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