Ground Glass Lesions on Chest Imaging: Evaluation of Reported Incidence in Cancer Patients Using Natural Language Processing.
Journal:
The Annals of thoracic surgery
PMID:
30612991
Abstract
BACKGROUND: Ground glass opacities (GGOs) on computed tomography (CT) have gained significant recent attention, with unclear incidence and epidemiologic patterns. Natural language processing (NLP) is a powerful computing tool that collects variables from unstructured data fields. Our objective was to characterize trends of GGO detection using NLP.