Development of a Natural Language Processing Engine to Generate Bladder Cancer Pathology Data for Health Services Research.

ABSTRACT:

Objective

To take the first step toward assembling population-based cohorts of patients with bladder cancer with longitudinal pathology data, we developed and validated a natural language processing (NLP) engine that abstracts pathology data from full-text pathology reports.

Methods

Using 600 bladder pathology reports randomly selected from the Department of Veterans Affairs, we developed and validated an NLP engine to abstract data on histology, invasion (presence vs absence and depth), grade, the presence of muscularis propria, and the presence of carcinoma in situ. Our gold standard was based on an independent review of reports by 2 urologists, followed by adjudication. We assessed the NLP performance by calculating the accuracy, the positive predictive value, and the sen

SUBMITTER: Schroeck FR 

PROVIDER: S-EPMC5696035 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature