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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
  • risk factors
  • electronic health record
  • big data
  • emergency department
  • oxidative stress
  • adipose tissue
  • skeletal muscle
  • adverse drug
  • chronic rhinosinusitis
  • weight loss