Automated Detection of Periprosthetic Joint Infections and Data Elements Using Natural Language Processing

摘要

Background: Periprosthetic joint infection (PJI) data elements are contained in both structured and unstructured documents in electronic health records and require manual data collection. The goal of this study is to develop a natural language processing (NLP) algorithm to replicate manual chart review for PJI data elements.