Application of artificial intelligence centric workflows for evaluation of neuroradiology emergencies

被引：1

作者：

Shakoor, Delaram ^{[1
]}

Al-Dasuqi, Khalid ^{[1
,2
]}

Cavallo, Joe ^{[1
]}

Ikuta, Ichiro ^{[1
,3
]}

Payabvash, Syedmehdi ^{[1
]}

Malhotra, Ajay ^{[1
,4
]}

机构：

[1] Yale Univ, Dept Radiol & Biomed Imaging, Sch Med, New Haven, CT USA

[2] Boston Childrens Hosp, Dept Radiol, Boston, MA USA

[3] Mayo Clin, Dept Radiol, Scottsdale, AZ USA

[4] Radiol & Biomed Imaging, POB 208042,Tompkins East 2, New Haven, CT 06520 USA

来源：

CLINICAL IMAGING | 2023年 / 101卷

关键词：

Artificial intelligence; Intracranial hemorrhage; Fractures; Detection;

D O I：

10.1016/j.clinimag.2023.04.004

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：

The goal of this study was to perform a pilot study to assess user-interface of radiologists with an artificial -intelligence (AI) centric workflow for detection of intracranial hemorrhage (ICH) and cervical spine fractures (CSFX). Over 12-month period, interaction and usage of AI software implemented in our institution, Aidoc, on head and cervical spine CT scans were obtained. Several interaction variables were defined, assessing different types of interaction between readers of different training level and AI software. The median usage of AI-centric workflow for detection of ICH and CSFX were 28.8% and 21.8%, respectively, demonstrating a significant additional engagement beyond Native workflow (worklist and PACS). Further studies are warranted to expand interaction assessments to further understand the value unlocked by the AI-centric workflows.

引用

页码：133 / 136

页数：4

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