Forecasting the Tuberculosis Incidence Using a Novel Ensemble Empirical Mode Decomposition-Based Data-Driven Hybrid Model in Tibet, China.

Jizhen LiYuhong LiMing YeSanqiao YaoChongchong YuLei WangWeidong WuYongbin Wang

Published in: Infection and drug resistance (2021)

This novel data-driven hybrid method can better consider both linear and nonlinear components in the TB incidence than the others used in this study, which is of great help to estimate and forecast the future epidemic trends of TB in Tibet. Besides, under present trends, strict precautionary measures are required to reduce the spread of TB in Tibet.

Keyphrases

mycobacterium tuberculosis
risk factors
pulmonary tuberculosis
emergency department
neural network
convolutional neural network
hiv aids