Clinical NLP

Clinical Natural Language Processing (NLP) focuses on developing computational methods to extract meaningful information from clinical text, aiming to improve healthcare efficiency and patient outcomes. Current research emphasizes adapting large language models (LLMs) for clinical tasks, exploring techniques like parameter-efficient fine-tuning and prompt engineering to overcome data scarcity and computational limitations; simpler transformer-based models trained from scratch also show promise in resource-constrained settings. These advancements hold significant potential for automating tasks like clinical note summarization, error detection, and information extraction, ultimately leading to more accurate diagnoses, improved treatment decisions, and enhanced research capabilities.