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Leveraging Natural Language Processing to Extract Features of Colorectal Polyps From Pathology Reports for Epidemiologic Study.

Ryzen BensonCandace WintertonMaci WinnBenjamin KrickMei LiuNoor Abu-El-RubMike ConwayGuilherme Del FiolAndrew J GawronSheetal Hardikar
Published in: JCO clinical cancer informatics (2023)
Our pipeline extracted histopathologic features of colorectal polyps from colonoscopy pathology reports, most notably individual polyp sizes, with considerable accuracy. This study demonstrates the utility of NLP for extracting polyp features and linking these data with EHR data to create an epidemiologic data set to study colorectal polyp risk factors and outcomes.
Keyphrases
  • electronic health record
  • risk factors
  • big data
  • oxidative stress
  • metabolic syndrome
  • adipose tissue
  • autism spectrum disorder
  • deep learning
  • artificial intelligence
  • anti inflammatory