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Llettuce: An Open Source Natural Language Processing Tool for the Translation of Medical Terms into Uniform Clinical Encoding

James Mitchell-White
Reza Omdivar
Esmond Urwin
Karthikeyan Sivakumar
Andy Rae
Xiaoyan Wang
Theresia Mina
John Chambers
Philip R Quinlan
Main:13 Pages
4 Figures
Bibliography:3 Pages
4 Tables
Abstract

This paper introduces Llettuce, an open-source tool designed to address the complexities of converting medical terms into OMOP standard concepts. Unlike existing solutions such as the Athena database search and Usagi, which struggle with semantic nuances and require substantial manual input, Llettuce leverages advanced natural language processing, including large language models and fuzzy matching, to automate and enhance the mapping process. Developed with a focus on GDPR compliance, Llettuce can be deployed locally, ensuring data protection while maintaining high performance in converting informal medical terms to standardised concepts.

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