Large language model-based information extraction from free-text radiology reports: a scoping review protocol

Abstract

Abstract Introduction Radiological imaging is one of the most frequently performed diagnostic tests worldwide. The free text contained in radiology reports is currently only rarely utilized for secondary use, including research and predictive analysis. However, this data might be made available by means of information extraction (IE), based on natural language processing (NLP). Recently, a new approach to NLP, large language models (LLMs), has gained momentum and continues to improve performance. The objective of this scoping review is to show the state of research regarding IE from free-text radiology reports based on LLMs, to investigate applied methods, and to guide future research by showing open challenges and limitations of current approaches. To our knowledge, no systematic nor scoping review of IE of radiology reports, based on LLMs, has been conducted yet. Existing publications are outdated and do not comprise LLM-based models. Methods and analysis This protocol is designed based on the JBI manual for evidence synthesis, chapter 11.2: “Development of a scoping review protocol”. Inclusion criteria and a search strategy comprising four databases (PubMed, IEEE Xplore, Web of Science Core Collection, ACM Digital Library) are defined. Furthermore, we describe the screening process, data charting, analysis and presentation of extracted data. Ethics and dissemination This protocol describes the methodology of a scoping literature review and does not comprise research on or with humans, animals or their data. Therefore, no ethical approval is required. After the publication of this protocol and the conduct of the review, its results are going to be published in an open access journal dedicated to biomedical informatics/ digital health. Strengths and limitations of this study This scoping review protocol strictly adheres to standardized guidelines for scoping review conduction, including JBI Manual for Evidence Synthesis and the PRISMA-ScR guideline. The search strategy comprises four databases: PubMed, IEEE Xplore, Web of Science Core Collection, and ACM Digital Library. This scoping review will close the knowledge gap present in the field of information extraction from radiology reports caused by the recent rapid technical process. According to the nature of a scoping review, identified sources of evidence are not critically appraised. The results of the scoping review will serve as a basis for defining further research directions regarding information extraction from radiology reports.

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