Clinical Note
Clinical notes, the cornerstone of patient care documentation, are increasingly the focus of research aimed at automating their creation and analysis to alleviate physician workload and improve care quality. Current research utilizes large language models (LLMs), often incorporating techniques like retrieval-augmented generation and fine-tuning strategies, to generate notes from various data sources, including doctor-patient conversations and existing records, and to extract key information for tasks such as phenotyping and diagnostic reasoning. This work is significant because it addresses the substantial administrative burden on healthcare professionals, potentially leading to improved efficiency, reduced burnout, and enhanced accuracy in diagnosis and treatment planning.
Papers
Intelligent Clinical Documentation: Harnessing Generative AI for Patient-Centric Clinical Note Generation
Anjanava Biswas, Wrick Talukdar
Edinburgh Clinical NLP at MEDIQA-CORR 2024: Guiding Large Language Models with Hints
Aryo Pradipta Gema, Chaeeun Lee, Pasquale Minervini, Luke Daines, T. Ian Simpson, Beatrice Alex