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March 3, 2026
Open Access
Automated abstraction of clinical parameters of multiple myeloma from real-world clinical notes using large language models
AC
Alana O'Brien Del Campo
DL
Dmytro Lituiev
Johnson & Johnson (United States)
GV
Gowtham Varma
Biogen (United States)
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Puntos clave
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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Campo et al. (Wed,) studied this question.
synapsesocial.com/papers/69a75bd2c6e9836116a23d57
https://doi.org/https://doi.org/10.1186/s12911-026-03345-z
Automated abstraction of clinical parameters of multiple myeloma from real-world clinical notes using large language models | Synapse