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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 1 of 1 Research Studies DisplayedPruitt P, Naidech A, Ornam J
A natural language processing algorithm to extract characteristics of subdural hematoma from head CT reports.
Researchers created a natural language processing (NLP) algorithm to predict radiographic characteristics of subdural hematomas (SDH). The NLP was used to extract data from cranial computed tomography (CT) scan reports for patients with SDH. The results were measured for accuracy compared to cranial CT scan interpretations by board-certified attending radiologists and data coded by two ED physicians.. Output performance was considered high, with an algorithm accuracy of 0.84 for side of largest SDH, 0.88 for thickness of largest SDH, and 0.92 for size of midline shift.
AHRQ-funded; HS000078.
Citation: Pruitt P, Naidech A, Ornam J .
A natural language processing algorithm to extract characteristics of subdural hematoma from head CT reports.
Emerg Radiol 2019 Jun;26(3):301-06. doi: 10.1007/s10140-019-01673-4..
Keywords: Diagnostic Safety and Quality, Imaging, Trauma