F Jungmann1, S Kuhn2, I Tsaur3, B Kämpgen4. 1. Klinik und Poliklinik für Diagnostische und Interventionelle Radiologie, Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Langenbeckstr. 1, 55131, Mainz, Deutschland. florian.jungmann@unimedizin-mainz.de. 2. Zentrum für Orthopädie und Unfallchirurgie, Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Mainz, Deutschland. 3. Klinik und Poliklinik für Urologie und Kinderurologie, Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Mainz, Deutschland. 4. Empolis Information Management GmbH, Kaiserslautern, Deutschland.
Abstract
BACKGROUND: The need for application expertise in natural language processing (NLP) is increasing in radiology. This way, in a complementary fashion to structured reporting using templates, the necessary database for quality assurance and continuous process optimization can be generated. OBJECTIVE: Possibilities and challenges of the application of NLP from the radiology point of view are explained. MATERIALS AND METHODS: The requirements and expectations for NLP systems are identified and demonstrated using a case study. RESULTS: For an effective use of this technology, NLP tasks for the interpretation of text using RadLex, an intuitive usage and feedback option as well as transparent quality of the NLP results are important. DISCUSSION: Using suitable NLP systems, targeted information can be extracted from large amounts of free text with manageable manual effort and high quality.
BACKGROUND: The need for application expertise in natural language processing (NLP) is increasing in radiology. This way, in a complementary fashion to structured reporting using templates, the necessary database for quality assurance and continuous process optimization can be generated. OBJECTIVE: Possibilities and challenges of the application of NLP from the radiology point of view are explained. MATERIALS AND METHODS: The requirements and expectations for NLP systems are identified and demonstrated using a case study. RESULTS: For an effective use of this technology, NLP tasks for the interpretation of text using RadLex, an intuitive usage and feedback option as well as transparent quality of the NLP results are important. DISCUSSION: Using suitable NLP systems, targeted information can be extracted from large amounts of free text with manageable manual effort and high quality.
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
Authors: Máté E Maros; Chang Gyu Cho; Andreas G Junge; Benedikt Kämpgen; Victor Saase; Fabian Siegel; Frederik Trinkmann; Thomas Ganslandt; Christoph Groden; Holger Wenz Journal: Sci Rep Date: 2021-03-09 Impact factor: 4.379
Authors: Maximilian König; André Sander; Ilja Demuth; Daniel Diekmann; Elisabeth Steinhagen-Thiessen Journal: PLoS One Date: 2019-11-27 Impact factor: 3.240