Comparison of Large Language Models with Rules-Based Natural Language Processing Algorithms for Extracting Data from Operative Notes

LLMs have the potential to impact clinical care, including the evaluation of electronic medical record free-text data. As registries serve as a cornerstone of orthopaedic evidence, this work demonstrates promise for LLMs to simplify, improve, and democratize the construction of registry databases from operative notes.

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Publication Details

Journal
Journal of Bone and Joint Surgery
Published
2026-03-24
DOI
https://doi.org/10.2106/jbjs.25.01338
Primary Topic
Digital Imaging in Medicine
Type
article
Field-Weighted Citation Impact
0.00
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article

Comparison of Large Language Models with Rules-Based Natural Language Processing Algorithms for Extracting Data from Operative Notes

Journal of Bone and Joint Surgery
Digital Imaging in Medicine
article

Comparison of Large Language Models with Rules-Based Natural Language Processing Algorithms for Extracting Data from Operative Notes

article en

Abstract

LLMs have the potential to impact clinical care, including the evaluation of electronic medical record free-text data. As registries serve as a cornerstone of orthopaedic evidence, this work demonstrates promise for LLMs to simplify, improve, and democratize the construction of registry databases from operative notes.

Journal of Bone and Joint Surgery
Mayo Clinic (US), Mayo Clinic in Florida (US)
Quality Education
Openalex Percentile: Top 13%
Digital Imaging in Medicine
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Comparison of Large Language Models with Rules-Based Natural Language Processing Algorithms for Extracting Data from Operative Notes · Journal of Bone and Joint Surgery (2026) | TGRS Research Map | TGRS