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Erschienen in: Journal of Digital Imaging 4/2020

29.05.2020 | Original Paper

Framework for Extracting Critical Findings in Radiology Reports

verfasst von: Thusitha Mabotuwana, Christopher S. Hall, Nathan Cross

Erschienen in: Journal of Imaging Informatics in Medicine | Ausgabe 4/2020

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Abstract

Critical results reporting guidelines demand that certain critical findings are communicated to the responsible provider within a specific period of time. In this paper, we discuss a generic report processing pipeline to extract critical findings within the dictated report to allow for automation of quality and compliance oversight using a production dataset containing 1,210,858 radiology exams. Algorithm accuracy on an annotated dataset having 327 sentences was 91.4% (95% CI 87.6–94.2%). Our results show that most critical findings are diagnosed on CT and MR exams and that intracranial hemorrhage and fluid collection are the most prevalent at our institution. 1.6% of the exams were found to have at least one of the ten critical findings we focused on. This methodology can enable detailed analysis of critical results reporting for research, workflow management, compliance, and quality assurance.
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Metadaten
Titel
Framework for Extracting Critical Findings in Radiology Reports
verfasst von
Thusitha Mabotuwana
Christopher S. Hall
Nathan Cross
Publikationsdatum
29.05.2020
Verlag
Springer International Publishing
Erschienen in
Journal of Imaging Informatics in Medicine / Ausgabe 4/2020
Print ISSN: 2948-2925
Elektronische ISSN: 2948-2933
DOI
https://doi.org/10.1007/s10278-020-00349-7

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