Improving the Quality of Unstructured Cancer Data Using Large Language Models: A German Oncological Case Study

Studies in health technology and informatics, vol. 316, pp. 685–689

Abstract

With cancer being a leading cause of death globally, epidemiological and clinical cancer registration is paramount for enhancing oncological care and facilitating scientific research. However, the heterogeneous landscape of medical data presents significant challenges to the current manual process of tumor documentation. This paper explores the potential of Large Language Models (LLMs) for transforming unstructured medical reports into the structured format mandated by the German Basic Oncology Dataset. Our findings indicate that integrating LLMs into existing hospital data management systems or cancer registries can significantly enhance the quality and completeness of cancer data collection - a vital component for diagnosing and treating cancer and improving the effectiveness and benefits of therapies. This work contributes to the broader discussion on the potential of artificial intelligence or LLMs to revolutionize medical data processing and reporting in general and cancer care in particular.

Authors 9

1. Yongli Mou corresponding Aachen Chair of Computer Science 5

   RWTH Aachen University

   Affiliation as printed

   Chair of Computer Science 5, RWTH Aachen University, Germany

2. J. Lehmkuhl Aachen Chair of Computer Science 5

   Fraunhofer Institute for Applied Information Technology · RWTH Aachen University

   Affiliation as printed

   Chair of Computer Science 5, RWTH Aachen University, Germany

   Fraunhofer FIT, Germany

3. Nicolas Sauerbrunn Aachen Center for Integrated Oncology

   Universitätsklinikum Aachen

   Affiliation as printed

   Center for Integrated Oncology, University Hospital Aachen, Germany

4. Anja Köchel Aachen Center for Integrated Oncology

   Universitätsklinikum Aachen

   Affiliation as printed

   Center for Integrated Oncology, University Hospital Aachen, Germany

5. Jens Panse Aachen Center for Integrated Oncology Department of Hematology, Oncology

   Universitätsklinikum Aachen

   Affiliation as printed

   Center for Integrated Oncology, University Hospital Aachen, Germany

   Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, University Hospital Aachen, Germany

6. Daniel Truh Aachen Department of Diagnostic and Interventional Radiology

   Universitätsklinikum Aachen

   Affiliation as printed

   Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Germany

7. Sulayman K. Sowe Aachen Chair of Computer Science 5

   Fraunhofer Institute for Applied Information Technology · RWTH Aachen University

   Affiliation as printed

   Chair of Computer Science 5, RWTH Aachen University, Germany

   Fraunhofer FIT, Germany

8. Tim H. Brümmendorf Aachen Department of Hematology, Oncology

   Universitätsklinikum Aachen

   Affiliation as printed

   Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, University Hospital Aachen, Germany

9. Stefan Decker Aachen Chair of Computer Science 5

   Fraunhofer Institute for Applied Information Technology · RWTH Aachen University

   Affiliation as printed

   Chair of Computer Science 5, RWTH Aachen University, Germany

   Fraunhofer FIT, Germany