In order to integrate heterogeneous clinical information sources, semantically correlating information entities have to be linked. Our discussions with radiologists revealed that anatomical entities with pathological findings are of particular interest when linking radiology text and images. Previous research to identify pathological findings focused on simplistic approaches that recognize diseases or negated findings, but failed to establish a holistic approach. In this paper, we introduce our syntacto-semantic parsing approach to classify sentences in radiology reports as either pathological or non-pathological based on the findings they describe. Although we operate with an incomplete, RadLex-based linguistic resource, the obtained results show the effectiveness of our approach by identifying a recall value of 74.3% for the classification task.
REF focused on the classification of sentences in radiology reports as either pathological and non-pathological based on the given findings.
Identifying Pathological Findings in German Radiology Reports Using a Syntacto-semantic Parsing Approach
BioNLP
Computer Science