Application of Machine Learning to Auto-Code Injury Data in the e-CHIRPP System: Development and Evaluation Study
The application of machine learning and auto-coding shows strong potential to benefit surveillance activities across various public health disciplines, yielding near real-time availability of intelligence, reduced administrative workload, continuous improvement, and adaptability to database growth and change.
Authors
- Tim Beattie (ORCID: https://orcid.org/0000-0003-3188-0592)
- Shamir Mukhi (ORCID: https://orcid.org/0009-0004-8245-1127)
- Wendy Thompson (ORCID: https://orcid.org/0000-0002-0177-998X)
- Steven McFaull (ORCID: https://orcid.org/0009-0009-2238-132X)
Institutions
- Public Health Agency of Canada (CA)
Publication Details
- Journal
- Online Journal of Public Health Informatics
- Published
- 2025-12-17
- DOI
- https://doi.org/10.2196/69143
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00