I. Introduction
Motivated by the escalating challenge of linking unstructured radiology reports with diagnoses within hospital information systems (HIS), this study addresses the crucial need to automate the analysis and classification of these reports. Unstructured diagnostic reports contain extensive descriptions that are crucial for determining the correct diagnosis and therapy. However, these descriptions are often complex and contain several types of findings, making them difficult to analyse and classify automatically.