Predicting the incidence of infectious diarrhea with symptom surveillance data using a stacking-based ensembled model

Predicting the incidence of infectious diarrhea with symptom surveillance data using a stacking-based ensembled model

Abstract Background Infectious diarrhea remains a major public health problem worldwide. This study used stacking ensemble to developed a predictive model for the incidence of infectious diarrhea, aiming to achieve better prediction performance. Methods Based on the surveillance data of infectious d...

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Bibliographic Details
Main Authors: Pengyu Wang, Wangjian Zhang, Hui Wang, Congxing Shi, Zhiqiang Li, Dahu Wang, Lei Luo, Zhicheng Du, Yuantao Hao
Format: Article
Language:English
Published: BMC 2024-02-01
Series:BMC Infectious Diseases
Subjects:
Infectious diarrhea
Prediction model
Ensemble learning
Stacking
Symptom surveillance
Online Access:https://doi.org/10.1186/s12879-024-09138-x

Internet

https://doi.org/10.1186/s12879-024-09138-x

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