Natural Language Processing for Information Extraction of Gastric Diseases and Its Application in Large-Scale Clinical Research.

ABSTRACT: Background and Aims: The utility of clinical information from esophagogastroduodenoscopy (EGD) reports has been limited because of its unstructured narrative format. We developed a natural language processing (NLP) pipeline that automatically extracts information about gastric diseases from unstructured EGD reports and demonstrated its applicability in clinical research. Methods: An NLP pipeline was developed using 2000 EGD and associated pathology reports that were retrieved from a single healthcare center. The pipeline extracted clinical information, including the presence, location, and size, for 10 gastric diseases from the EGD reports. It was validated with 1000 EGD reports by evaluating sensitivity, positive predictive value (PPV), accuracy, and F1 score. The pipeline w

SUBMITTER: Song G 

PROVIDER: S-EPMC9181010 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature