Identification of Non-Lexical Content in Croatian Health Forum Entries

Medical texts often contain expressions that are not listed in biomedical dictionaries and terminology systems. In this investigation, the detection of such entities is examined with online health forum entries in the Croatian language. Emphasis is put on short-form content, lexical variations, brand names, and proper names. By leveraging Transformer architectures on token and entity level, noteworthy results (>90% in F1-measure) could be achieved, which is on par with state-of-the-art named entity recognition in high-resource languages. Additionally, this investigation showcases a way to recognize non-lexicalized tokens from texts, which can be of use for further research questions in combination with word sense disambiguation, word-embeddings, and terminology expansion workflows.