Large-scale identification of undiagnosed hepatic steatosis using natural language processing.

ABSTRACT:

Background

Nonalcoholic fatty liver disease (NAFLD) is a major cause of liver-related morbidity in people with and without diabetes, but it is underdiagnosed, posing challenges for research and clinical management. Here, we determine if natural language processing (NLP) of data in the electronic health record (EHR) could identify undiagnosed patients with hepatic steatosis based on pathology and radiology reports.

Methods

A rule-based NLP algorithm was built using a Linguamatics literature text mining tool to search 2.15 million pathology report and 2.7 million imaging reports in the Penn Medicine EHR from November 2014, through December 2020, for evidence of hepatic steatosis. For quality control, two independent physicians manually reviewed randomly chosen biopsy and imagi

SUBMITTER: Schneider CV 

PROVIDER: S-EPMC10432816 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature