Influenza time series prediction models in a megacity from 2010 to 2019: Based on seasonal autoregressive integrated moving average and deep learning hybrid prediction model-Reference-Cited by-同舟云学术

Influenza time series prediction models in a megacity from 2010 to 2019: Based on seasonal autoregressive integrated moving average and deep learning hybrid prediction model

Published:2024-08-09 Issue: Volume: Page:
ISSN:0366-6999
Container-title:Chinese Medical Journal
language:en
Short-container-title:

Author:

Yang Jin¹²,Yang Liuyang²³,Li Gang⁴,Du Jing⁴,Ma Libing²⁵,Zhang Ting²,Zhang Xingxing²,Yang Jiao²,Feng Luzhao²,Yang Weizhong²,Wang Chen²⁶

Affiliation:

1. Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong 510515, China

2. School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China

3. The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, Yunnan 650106, China

4. Beijing Centre for Disease Prevention and Control, Beijing 100013, China

5. Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Guilin Medical University, Guilin, Guizhou 561113, China

6. National Clinical Research Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing 100029, China

Publisher

Ovid Technologies (Wolters Kluwer Health)

Reference3 articles.

1. Establishment of multi-point trigger and multi-channel surveillance mechanism for intelligent early warning of infectious diseases in China (in Chinese);Yang;Chin J Epidemiol,2020

2. Predicting seasonal influenza based on SARIMA model, in mainland China from 2005 to 2018;Cong;Int J Environ Res Public Health,2019

3. The prediction of influenza-like illness and respiratory disease using LSTM and ARIMA;Tsan;Int J Environ Res Public Health,2022