Biomedical Text Mining

Biomedical text mining uses computational methods to extract meaningful information from the vast body of biomedical literature. Current research focuses on developing and refining advanced language models, such as BERT and its biomedical variants (e.g., BioBERT, BioMamba), to improve tasks like named entity recognition, relation extraction, and question answering. These advancements are crucial for accelerating scientific discovery, enabling more efficient literature reviews, and facilitating the development of new diagnostic and therapeutic tools. The field also emphasizes efficient model architectures and strategies for handling diverse languages and limited data resources.