Developing and Assessing Multilingual NLP Applications in Biomedicine
Abstract
Recent developments in language technology, particularly the use of large language models, have sparked interest and introduced new trends in biomedical and clinical natural language processing (NLP), addressing the challenges of processing complex and diverse biomedical data. We will summarize recent strategies and results in biomedical literature mining and its connection to clinical NLP, as well as highlight the adaptation of Spanish resources for multilingual scenarios. Additionally, we will discuss the importance of shared tasks and high-quality annotated datasets for fostering technological advancements and assessing the quality of automated results in clinical NLP. Finally, we will introduce ongoing application scenarios in biomaterials research (BIOMATDB), clinical cardiology (DataTools4Heart & AI4HF), rare diseases/rheumatology (BARITONE), and occupational health (AI4ProfHealth).
