Coding free text radiology reports using the Cancer Text Information Extraction System (caTIES)
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Updated: Jul 2, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
David Carrell1, Diana Miglioretti, Rebecca Smith-Bindman
1Group Health Cooperative, Center for Health Studies, Seattle, WA, USA.
Abstract:
We coded 700 radiology reports from 373 women using an unmodified deployment of the Cancer Text Information Extraction System (caTIES), a publicly-available tool using natural language processing techniques. We were moderately successfully using caTIES for case ascertainment, successfully identifying 9/11 of a random sample of cancer case (sensitivity 82%) and 5/100 controls (specificity 95%) We are currently developing a classification scheme to assess clinical risk of ovarian cancer and identifying required extensions to caTIES algorithms.
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