Automated abstraction of clinical parameters of multiple myeloma from real-world clinical notes using large language models

Key Points

• Automated abstraction of clinical parameters is achieved from real-world notes.
• Key evidence shows that natural language processing methods improve data extraction efficiency.
• Analysis of clinical notes using large language models reveals significant insights into patient care.
• This method may enable better clinical decision-making based on refined data extraction, but requires further validation.