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Natural language processing to identify ureteric stones in radiology reports
29
Zitationen
2
Autoren
2019
Jahr
Abstract
Our NLP tool demonstrated high specificity but low sensitivity at identifying CT KUB reports that are positive for ureteric stones. This was attributable to the lack of feature extraction tools tailored for analysing radiology text, incompleteness of the medical lexicon database and heterogeneity of unstructured reports. Improvements in these areas will help improve data extraction accuracy.
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