Setting up standards: A methodological proposal for pediatric Triage machine learning model construction based on clinical outcomes
作者：
Highlights：
• We deal with triage prediction systems using machine learning in pediatric patients.
• A very large in-house dataset was used for model construction and validation.
• We propose a data re-labeling process aiming to improve clinical outcome prediction.
• Random forest provides best results over a bunch of multi-class performance metrics.
• This result outperforms traditional Triage models.
摘要
•We deal with triage prediction systems using machine learning in pediatric patients.•A very large in-house dataset was used for model construction and validation.•We propose a data re-labeling process aiming to improve clinical outcome prediction.•Random forest provides best results over a bunch of multi-class performance metrics.•This result outperforms traditional Triage models.
论文关键词：Machine learning,Emergency department,Triage,Data science,Clinical decision support systems
论文评审过程：Received 19 January 2019, Revised 23 April 2019, Accepted 2 July 2019, Available online 5 July 2019, Version of Record 19 July 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.07.005
