Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning–Based Text-Mining Approach

Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning–Based Text-Mining Approach

BackgroundUnintentional injury is the leading cause of death in young children. Emergency department (ED) diagnoses are a useful source of information for injury epidemiological surveillance purposes. However, ED data collection systems often use free-text fields to report pa...

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Bibliographic Details
Main Authors: Danila Azzolina, Silvia Bressan, Giulia Lorenzoni, Giulia Andrea Baldan, Patrizia Bartolotta, Federico Scognamiglio, Andrea Francavilla, Corrado Lanera, Liviana Da Dalt, Dario Gregori
Format: Article
Language:English
Published: JMIR Publications 2023-07-01
Series:JMIR Public Health and Surveillance
Online Access:https://publichealth.jmir.org/2023/1/e44467

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https://publichealth.jmir.org/2023/1/e44467

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