Code for: Trends in Diagnostic Terminology and Consensus Adoption in Fracture-Related Infection Literature: A Contextual Text Mining Analysis

Published: 15 April 2026| Version 1 | DOI: 10.17632/bc5vsrfrv6.1
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Description

This repository contains the code used for the analysis in: “Trends in Diagnostic Terminology and Consensus Adoption in Fracture-Related Infection Literature: A Contextual Text Mining Analysis.” It is a context-aware LLM pipeline for counting fracture-related infection (FRI) terminology in full-text PDFs. It was designed to reduce misleading term matches where a keyword appears in text but is not actually being used to diagnose, classify, or describe infection. The development version of the code is available on GitHub: https://github.com/nickpiccaro/FRI-LLM-Based-Text-Mining. This archived version corresponds to the version used for manuscript submission.

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Steps to reproduce

Step-by-step instructions to reproduce the analysis, including data preparation, environment setup, and execution of scripts, are provided in the included README.md file.

Categories

Medicine, Infectious Disease, Orthopedics, Data Science, Natural Language Processing, Text Mining

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