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.
Keywords: Artificial intelligence; Decision support; Evaluation; Quality assurance; RadLex.