A multivariate multi-step LSTM forecasting model for tuberculosis incidence with model explanation in Liaoning Province, China

A multivariate multi-step LSTM forecasting model for tuberculosis incidence with model explanation in Liaoning Province, China

Abstract Background Tuberculosis (TB) is the respiratory infectious disease with the highest incidence in China. We aim to design a series of forecasting models and find the factors that affect the incidence of TB, thereby improving the accuracy of the incidence prediction. Results In this paper, we...

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Bibliographic Details
Main Authors: Enbin Yang, Hao Zhang, Xinsheng Guo, Zinan Zang, Zhen Liu, Yuanning Liu
Format: Article
Language:English
Published: BMC 2022-05-01
Series:BMC Infectious Diseases
Subjects:
Tuberculosis
Machine learning
Multivariate multi-step LSTM model
Hybrid forecasting model
Model explanation
SHAP
Online Access:https://doi.org/10.1186/s12879-022-07462-8

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