Clinical Information Extraction

Clinical information extraction (CIE) focuses on automatically extracting structured data from unstructured clinical text, such as medical reports and notes, to improve efficiency and data analysis. Current research heavily utilizes large language models (LLMs), particularly transformer-based architectures like BERT and its variants, along with techniques like prompt engineering and few-shot learning, to achieve high accuracy in extracting various clinical concepts and relations. This field is crucial for advancing clinical research, improving healthcare decision-making, and facilitating the development of clinical decision support systems by transforming readily available but difficult-to-analyze textual data into usable structured formats.