Biomedical NLP Task

Biomedical natural language processing (NLP) focuses on developing computational methods to analyze and understand biomedical text, aiming to extract knowledge, improve information retrieval, and facilitate clinical decision-making. Current research heavily emphasizes the application of large language models (LLMs), including both generative (like GPT) and encoder-decoder architectures (like BART and T5), often augmented with retrieval mechanisms to improve accuracy and address issues like hallucinations. These models are being fine-tuned and instruction-tuned for various biomedical tasks such as relation extraction, question answering, and entity linking, with a growing interest in multilingual and multi-task learning approaches. The ultimate goal is to leverage these advancements to improve efficiency and accuracy in biomedical research and healthcare, enabling faster scientific discovery and better patient care.