Biomedical Text

Biomedical text analysis focuses on extracting meaningful information from the vast and growing body of scientific literature and clinical records. Current research heavily utilizes deep learning models, particularly transformer-based architectures like BERT and its biomedical variants, along with Retrieval Augmented Generation (RAG) methods to improve accuracy and explainability. These advancements enable tasks such as automated literature review, hypothesis generation, and the creation of accessible summaries for non-experts, ultimately accelerating scientific discovery and improving healthcare information access.