AIMC Topic: Epidemics
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A Deep Learning Framework for Using Search Engine Data to Predict Influenza-Like Illness and Distinguish Epidemic and Nonepidemic Seasons: Multifeature Time Series Analysis.
Journal of medical Internet research
Aug 11, 2025
BACKGROUND: The seasonal influenza epidemic poses a persistent and severe threat to global public health. Web-based search data are recognized as a valuable source for forecasting influenza or other respiratory tract infection epidemics. Current infl...
Oropouche fever outbreak in Brazil: Key factors behind the largest epidemic in history.
PloS one
Jul 28, 2025
Oropouche virus (OROV) is an arthropod-borne virus responsible for outbreaks of Oropouche fever (ORO) in Central and South America since the 1950s. Herein, we investigated the climatic and socioenvironmental factors contributing to the reemergence of...
Spatio-temporal epidemic forecasting using mobility data with LSTM networks and attention mechanism.
Scientific reports
Mar 20, 2025
The outbreak of infectious diseases can have profound impacts on socio-economic balances globally. Accurate short-term forecasting of infectious diseases is crucial for policymakers and healthcare systems. This study proposes a novel deep learning ap...
Artificial intelligence for modelling infectious disease epidemics.
Nature
Feb 19, 2025
Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social sci...
Multi-region infectious disease prediction modeling based on spatio-temporal graph neural network and the dynamic model.
PLoS computational biology
Jan 9, 2025
Human mobility between different regions is a major factor in large-scale outbreaks of infectious diseases. Deep learning models incorporating infectious disease transmission dynamics for predicting the spread of multi-regional outbreaks due to human...
A Physics-Informed Neural Network approach for compartmental epidemiological models.
PLoS computational biology
Sep 5, 2024
Compartmental models provide simple and efficient tools to analyze the relevant transmission processes during an outbreak, to produce short-term forecasts or transmission scenarios, and to assess the impact of vaccination campaigns. However, their ca...
Global Research on Pandemics or Epidemics and Mental Health: A Natural Language Processing Study.
Journal of epidemiology and global health
Aug 8, 2024
BACKGROUND: The global research on pandemics or epidemics and mental health has been growing exponentially recently, which cannot be integrated through traditional systematic review. Our study aims to systematically synthesize the evidence using natu...
Leveraging advances in data-driven deep learning methods for hybrid epidemic modeling.
Epidemics
Jun 24, 2024
Mathematical modeling of epidemic dynamics is crucial to understand its underlying mechanisms, quantify important parameters, and make predictions that facilitate more informed decision-making. There are three major types of models: mechanistic model...
DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction.
PLoS computational biology
Apr 10, 2024
In the midst of an outbreak or sustained epidemic, reliable prediction of transmission risks and patterns of spread is critical to inform public health programs. Projections of transmission growth or decline among specific risk groups can aid in opti...
Hallucinating hallucinogens.
Science (New York, N.Y.)
Nov 9, 2023
Fighting the designer drug epidemic with generative AI.
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