This paper is in the following e-collection/theme issue:

Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (1001) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1142) AI Applications in Public Health (31) Secondary Use of Clinical Data for Research and Surveillance (475) Machine Learning (2095) Influenza and Influenza-Like-Illness (ILI) Surveillance (237) Artificial Intelligence (2162)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71786, first published .
A Deep Learning Framework for Using Search Engine Data to Predict Influenza-Like Illness and Distinguish Epidemic and Nonepidemic Seasons: Multifeature Time Series Analysis

A Deep Learning Framework for Using Search Engine Data to Predict Influenza-Like Illness and Distinguish Epidemic and Nonepidemic Seasons: Multifeature Time Series Analysis

A Deep Learning Framework for Using Search Engine Data to Predict Influenza-Like Illness and Distinguish Epidemic and Nonepidemic Seasons: Multifeature Time Series Analysis

Authors of this article:

Ji Li1, 2 Author Orcid Image ;   Xiangyu Yan1 Author Orcid Image ;   Xingjie Chu3 Author Orcid Image ;   Ying Zhang4 Author Orcid Image ;   Guoliang Liu3 Author Orcid Image ;   Lin Li4 Author Orcid Image ;   Yue Li1, 2 Author Orcid Image ;   Xiaochun Dong4 Author Orcid Image ;   Zihan Mei1 Author Orcid Image ;   Zhengkun Liu1 Author Orcid Image ;   Jinyue Yuan1 Author Orcid Image ;   Xiaohan Sun1 Author Orcid Image ;   Chunxia Cao1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Wang Y, Zhai S, Wu C, Chen B, Zhang W, Li J, Cheng X, Xiao L. Dynamic ensemble deep learning with multi-source data for robust influenza forecasting in Yangzhou. BMC Public Health 2025 View