Background Web-based sources are increasingly employed in the analysis, detection, and
forecasting of diseases and epidemics, and in predicting human behavior toward several …

Twitter is a social media platform where over 500 million people worldwide publish their
ideas and discuss diverse topics, including their health conditions and public health events …

Forecasting influenza-like illness (ILI) is of prime importance to epidemiologists and health-
care providers. Early prediction of epidemic outbreaks plays a pivotal role in disease …

The remarkable upsurge of social media has dramatic impacts on health care research and
practice. Social media are resha** health information management in a variety of ways …

Background The popularity and proliferation of online social networks (OSNs) have created
massive social interaction among users that generate an extensive amount of data. An OSN …

Background Infectious disease outbreaks have the potential to cause a high number of
fatalities and are a very serious public health risk. Objectives Our aim was to utilise an …

Background Emerging and re-emerging infectious diseases are a significant public health
concern, and early detection and immediate response is crucial for disease control. These …

We propose a novel data-driven machine learning method using long short-term memory
(LSTM)-based multi-stage forecasting for influenza forecasting. The novel aspects of the …

Influenza epidemic is a serious public health problem that has attracted worldwide attention
due to cause cases of severe illness, an enormous economic burden, and even deaths …

Abstract The World Health Organization (WHO) declared on 11th March 2020 the spread of
the coronavirus disease 2019 (COVID-19) a pandemic. The traditional infectious disease …