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OBJECTIVE The majority of radiological reports are still written as free text and lack structure. Further evaluation of free-text reports is difficult to achieve without a great deal of manual effort, and is not possible in everyday clinical practice. This study aims to automatically capture clinical information and positive hit rates from narrative radiological reports of suspected urolithiasis using natural language processing (NLP). METHODS Narrative reports of low dose computed tomography (CT) of the retroperitoneum from April 2016
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