Use of natural language processing techniques to predict patient selection for total hip and knee arthroplasty from radiology reports.

Journal: The bone & joint journal

Published Date: Jul 1, 2024

Abstract

AIMS: To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology reports.

Authors

Luke Farrow

University of Aberdeen, Aberdeen, UK.
Mingjun Zhong

University of Aberdeen, Aberdeen, UK.
Lesley Anderson

University of Aberdeen, Aberdeen, UK.

Keywords

Aged Algorithms Arthroplasty, Replacement, Hip Arthroplasty, Replacement, Knee Artificial Intelligence Female Humans Male Middle Aged Natural Language Processing Patient Selection

External Resources

View on PubMed Access via DOI PubMed (38945535)

Use of natural language processing techniques to predict patient selection for total hip and knee arthroplasty from radiology reports.

Abstract

Authors

Keywords

External Resources

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