F Jungmann1, S Kuhn2, B Kämpgen3. 1. Klinik und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsmedizin, Johannes Gutenberg-Universität Mainz, Langenbeckstr. 1, 55131, Mainz, Deutschland. florian.jungmann@unimedizin-mainz.de. 2. Zentrum für Orthopädie und Unfallchirurgie, Universitätsmedizin, Johannes Gutenberg-Universität Mainz, Mainz, Deutschland. 3. Empolis Information Management GmbH, Technologiepark Würzburg-Rimpar, 97222, Rimpar, Deutschland.
Abstract
BACKGROUND: Due to the increasing demands in radiology, applications that enable quality assurance and continuous process optimization are required. OBJECTIVE: The 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 METHODS: The 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. RESULTS: In our case study, NLP proved to be a helpful, automated tool for internal quality testing. DISCUSSION: NLP offers numerous application scenarios for decision support and for quality management in radiology.
BACKGROUND: Due to the increasing demands in radiology, applications that enable quality assurance and continuous process optimization are required. OBJECTIVE: The 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 METHODS: The 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. RESULTS: In our case study, NLP proved to be a helpful, automated tool for internal quality testing. DISCUSSION: NLP offers numerous application scenarios for decision support and for quality management in radiology.
Authors: Dhakshinamoorthy Ganeshan; Phuong-Anh Thi Duong; Linda Probyn; Leon Lenchik; Tatum A McArthur; Michele Retrouvey; Emily H Ghobadi; Stephane L Desouches; David Pastel; Isaac R Francis Journal: Acad Radiol Date: 2017-10-10 Impact factor: 3.173
Authors: Florian Jungmann; G Arnhold; B Kämpgen; T Jorg; C Düber; P Mildenberger; R Kloeckner Journal: J Digit Imaging Date: 2020-08 Impact factor: 4.056