Machine Learning to Prioritize High-Severity Patient Safety Events for Institutional Investigation: Algorithm Development and Validation Study.
- DOI
- 10.2196/101393
- Published
- 2026 Sep 29
- Container
- JMIR medical informatics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.2196/101393,
title = {Machine Learning to Prioritize High-Severity Patient Safety Events for Institutional Investigation: Algorithm Development and Validation Study.},
author = {Chen H and Islam S and Pozzobon LD and Chartier LB and Cohen E},
year = {2026},
journal = {JMIR medical informatics},
doi = {10.2196/101393},
url = {https://doi.org/10.2196/101393}
}RIS
TY - JOUR TI - Machine Learning to Prioritize High-Severity Patient Safety Events for Institutional Investigation: Algorithm Development and Validation Study. AU - Chen H AU - Islam S AU - Pozzobon LD AU - Chartier LB AU - Cohen E PY - 2026 JO - JMIR medical informatics DO - 10.2196/101393 UR - https://doi.org/10.2196/101393 ER -
APA
H, C., S, I., LD, P., LB, C., & E, C. (2026). Machine Learning to Prioritize High-Severity Patient Safety Events for Institutional Investigation: Algorithm Development and Validation Study.. JMIR medical informatics. https://doi.org/10.2196/101393
Source records
- pubmed · retrieved 2026-11-10T09:21:23.922Z