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January 28, 2026BMC Medical Informatics and Decision MakingOpen Access

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

Alana O'Brien Del Campo Dmytro Lituiev Gowtham Varma Mithun Manoharan Sunil Kumar Ravi Avinash Aman Ankit Kansagra Joel Greshock A J Venkatakrishnan Ashita S. Batavia

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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.

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Implication

Observational analysis extracts clinical parameters from real-world notes in multiple myeloma, suggesting enhanced data utilization.

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Cite This Study

Campo et al. (2026) studied this question.

synapsesocial.com/papers/69a75bd2c6e9836116a23d57 https://doi.org/10.1186/s12911-026-03345-z

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