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Updated: Dec 28, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Using the "Who, What, and When" of free text documentation to improve hospital infectious disease surveillance
Philip Zachariah1, Alexandra Hill-Ricciuti2, Lisa Saiman1
1Department of Pediatrics, Columbia University Irving Medical Center, New York, NY; Department of Infection Prevention & Control, NewYork-Presbyterian Hospital, New York, NY.
Abstract:
We demonstrate a novel method of using unstructured health data for infectious disease surveillance. A model incorporating the dynamics of documentation of a test diagnosis (UTI) in free text, without using grammatical or syntactic analysis, achieved performance comparable to ICD-10 codes (sensitivity 57.3, positive predictive value 69.5%, negative predictive value 95.9%) and detected missed cases (15% of total).
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