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- F Jungmann, S Kuhn, and B Kämpgen.
- Klinik und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsmedizin, Johannes Gutenberg-Universität Mainz, Langenbeckstr. 1, 55131, Mainz, Deutschland. florian.jungmann@unimedizin-mainz.de.
- Radiologe. 2018 Aug 1; 58 (8): 764-768.
BackgroundDue to the increasing demands in radiology, applications that enable quality assurance and continuous process optimization are required.ObjectiveThe principles of Natural Language Processing (NLP) as a computer-based method for structuring of free text reports are explained and application scenarios are sketched.Materials Und MethodsThe structuring of free texts succeeds by several theories, linguistic techniques (word meanings, word context, negations), statistical methods with rules and currently with deep learning approaches. Medical encyclopedias, such as RadLex®, are suitable for coding findings. NLP was used in our own radiology clinic to check the quality of 3756 CT reports.ResultsIn our case study, NLP proved to be a helpful, automated tool for internal quality testing.DiscussionNLP offers numerous application scenarios for decision support and for quality management in radiology.
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