Application of artificial intelligence centric workflows for evaluation of neuroradiology emergencies

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 implemente...

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Bibliographic Details
Published in:	Clinical imaging Vol. 101; pp. 133 - 136
Main Authors:	Shakoor, Delaram, Al-Dasuqi, Khalid, Cavallo, Joe, Ikuta, Ichiro, Payabvash, Syedmehdi, Malhotra, Ajay
Format:	Journal Article
Language:	English
Published:	United States Elsevier Inc 01-09-2023
Subjects:	Artificial intelligence Detection Fractures Intracranial hemorrhage Intracranial hemorrhage Fractures Detection Artificial intelligence
Online Access:	Get full text
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Summary:	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. •The median additional interaction with the AI-centric workflow for intracranial hemorrhage was 28.8%.•The median additional interaction with the AI-centric workflow for cervical spine fractures was 21.8%.•Comparing the interactions of trainees versus attendings for head CTs, median of PDC was significantly higher for faculty.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0899-7071 1873-4499
DOI:	10.1016/j.clinimag.2023.04.004