Biomedical Text Summarization

Biomedical text summarization aims to automatically generate concise and accurate summaries of complex medical texts, improving access to crucial information for clinicians and researchers. Current research focuses on enhancing the accuracy and factual consistency of these summaries using advanced techniques like pointer networks within transformer models, incorporating knowledge from cited papers and external knowledge bases, and employing various pre-training strategies to improve performance on domain-specific tasks. These advancements are crucial for efficiently managing the ever-growing volume of biomedical literature and electronic health records, ultimately improving healthcare and scientific discovery.