Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Repeat self-harm hospitalizations in Canada: a survival analysis.

Injury epidemiology·2025
Same author

Self-harm hospitalizations and neighbourhood level material and social deprivation in Canada: an ecological study.

BMC psychiatry·2024
Same author

Self-harm and rurality in Canada: an analysis of hospitalization data from 2015 to 2019.

Social psychiatry and psychiatric epidemiology·2023
Same author

Physical Activity, Sedentary Behavior, and Sleep on Twitter: Multicountry and Fully Labeled Public Data Set for Digital Public Health Surveillance Research.

JMIR public health and surveillance·2022
Same author

Crowdsourcing for Machine Learning in Public Health Surveillance: Lessons Learned From Amazon Mechanical Turk.

Journal of medical Internet research·2022
Same journal

Burden of Stroke in China From 1990 to 2023: Analysis From the Global Burden of Disease Study 2023.

Online journal of public health informatics·2026
Same journal

Tweets Surrounding Pharmaceutical Drug Brands With Top Direct-to-Consumer TV-Advertising Budgets: Social Media Listening Study.

Online journal of public health informatics·2026
Same journal

The Use of Tomographs in Brazil's National Health System: Case Study on the Efficiency of the Public Network in Rio Grande do Norte.

Online journal of public health informatics·2026
Same journal

Transforming Pediatric Care Through AI: Bridging the Digital Divide in Health Informatics.

Online journal of public health informatics·2026
Same journal

Building Enhanced Public Health Data Systems With a Situational Awareness and Learning Tool: Focus Group Study.

Online journal of public health informatics·2026
Same journal

Assessment of the Cultural Nuances in COVID-19 Vaccine Uptake Through a Comparative Analysis of English and Spanish Facebook Posts in Tarrant County, Texas: Longitudinal Study.

Online journal of public health informatics·2026
See all related articles

Related Experiment Video

Updated: Jan 8, 2026

Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device
06:51

Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device

Published on: July 29, 2016

8.2K

Application of Machine Learning to Auto-Code Injury Data in the e-CHIRPP System: Development and Evaluation Study.

Shamir N Mukhi1, Steven R McFaull2, Wendy Thompson2

  • 1Canadian Network for Public Health Intelligence, Public Health Agency of Canada, 9700 Jasper Ave, Edmonton, AB, T5J 4C3, Canada, 1-204-771-4698.

Online Journal of Public Health Informatics
|December 17, 2025
PubMed
Summary
This summary is machine-generated.

Machine learning accurately auto-codes injury data from patient narratives, improving public health surveillance timeliness and reducing administrative burden. This enhances the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) system.

Keywords:
auto-codinginformaticsinjurymachine learningpoisoningpublic healthsurveillance

More Related Videos

Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion
08:13

Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion

Published on: January 20, 2019

7.0K
Author Spotlight: Insight Into Innovations in Spinal Cord Injury Research
06:31

Author Spotlight: Insight Into Innovations in Spinal Cord Injury Research

Published on: January 19, 2024

2.7K

Related Experiment Videos

Last Updated: Jan 8, 2026

Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device
06:51

Development of an Algorithm to Perform a Comprehensive Study of Autonomic Dysreflexia in Animals with High Spinal Cord Injury Using a Telemetry Device

Published on: July 29, 2016

8.2K
Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion
08:13

Development and Implementation of a Multi-Disciplinary Technology Enhanced Care Pathway for Youth and Adults with Concussion

Published on: January 20, 2019

7.0K
Author Spotlight: Insight Into Innovations in Spinal Cord Injury Research
06:31

Author Spotlight: Insight Into Innovations in Spinal Cord Injury Research

Published on: January 19, 2024

2.7K

Area of Science:

  • Public Health Informatics
  • Machine Learning Applications
  • Injury Surveillance Systems

Background:

  • The Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) is a key injury surveillance system in Canada, collecting over 4 million records since 1990.
  • Manual coding of injury data within the e-CHIRPP system is administratively burdensome and causes significant delays in reporting.

Purpose of the Study:

  • To implement machine learning for auto-coding injury data based on patient narratives.
  • To enhance the timeliness of surveillance findings and improve adaptability within the e-CHIRPP system.

Main Methods:

  • Machine learning algorithms were assessed for classifying and auto-coding injury data extracted from the e-CHIRPP system.
  • A chosen algorithm was evaluated on 2-year and 7-year datasets, with inaccuracies investigated for process refinement.

Main Results:

  • Auto-coding demonstrated high accuracy compared to manual coding for most injury variables.
  • Identified sources of inaccuracies provided insights for ongoing process improvement and refinement.

Conclusions:

  • Machine learning-based auto-coding offers significant potential for public health surveillance.
  • Benefits include near real-time intelligence, reduced administrative workload, and enhanced system adaptability.