Text mining in radiology reports

Text mining is a popular research topic with application areas ranging from security to media and marketing. More specifically, text mining has been applied in biomedical area for the categorization of radiology reports, which is a challenging problem due to their free-text and unstructured format. State-of-the-art in radiology report mining has mostly focused on English text, while studies on Turkish reports are scarce. Accordingly, in this work we propose to employ text mining for categorization of Turkish radiology reports. We automatically remove header and footer of the reports, apply frequency analysis on the remaining report text, and perform categorization of reports to anatomical regions using pre-selected keywords. The accuracy of the proposed solution is measured as 84.3% over a 66-report test set.