AI tools in Emergency Radiology reading room: a new era of Radiology

被引：4

作者：

Dundamadappa, Sathish Kumar ^{[1
]}

机构：

[1] UMass Chan Med Sch, UMass Mem Med Ctr, 55 Lake Ave North, Worcester, MA 01655 USA

来源：

EMERGENCY RADIOLOGY | 2023年 / 30卷 / 05期

关键词：

Deep learning; AI algorithms; ER radiology; Opportunistic screening; ARTIFICIAL-INTELLIGENCE; CT; SCINTIGRAPHY; RADIOGRAPHS; FRACTURES; HEALTH;

D O I：

10.1007/s10140-023-02154-5

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

Artificial intelligence tools in radiology practices have surged, with modules developed to target specific findings becoming increasingly prevalent and proving valuable in the daily emergency room radiology practice. The number of US Food and Drug Administration-cleared radiology-related algorithms has soared from just 10 in early 2017 to over 200 presently. This review will concentrate on the present utilization of AI tools in clinical ER radiology setting, including a brief discussion of the limitations of the technique. As radiologists, it is essential that we embrace this technology, comprehend its constraints, and use it to improve patient care.

引用

页码：647 / 657

页数：11

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