Artificial intelligence for modelling infectious disease epidemics

2025/02/19 by Moritz U. G. Kraemer, Joseph L.-H. Tsui, Serina Chang +41 · 2 voices · 12 citations
Mathematics · Medicine · #COVID-19 epidemiological studies #Data-Driven Disease Surveillance #Viral Infections and Outbreaks Research

paper · doi:10.1038/s41586-024-08564-w

Citations

• Understanding deep learning (still) requires rethinking generalization
• Calibration: the Achilles heel of predictive analytics
• A decoder-only foundation model for time-series forecasting
• Using sequences of life-events to predict human lives

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• Revolutionizing infectious disease surveillance: Multi-omics technologies and AI-driven integration
• The behavioral spillover effect: Modeling behavioral interdependencies in multi-pathogen dynamics
• Deep learning framework for predicting stochastic take-off and die-out of early spreading
• The potential roles for artificial intelligence in supporting veterinarians during an emergency response
• Middle powers must collaborate on health data and health AI is imperative
• Rebalancing power in infectious disease modelling: Toward inclusive and contextual approaches
• How ready are we to use artificial intelligence in our fight against antimicrobial resistance? An ESGAID and EAAS perspective
• Enhancing epidemic forecast usability for policymakers: A global mixed-methods study
• Generative AI-Driven Decision-Making for Disease Control and Pandemic Preparedness Model 4.0 in Rural Communities of Bangladesh: Management Informatics Approach

Discussions

• This week our #JournalClub looked at some of the potential areas for using "Artificial intelligence for modelling infectious disease epidemics" in a recently published paper by @mugkraemer.bsky.social [bsky, 3 points, 0 comments]
• Find the journal publications of this work by @mugkraemer.bsky.social and team in @natureportfolio.nature.com doi.org/10.1038/s415... @imperialcollegeldn.bsky.social @imperialsph.bsky.social @thom [bsky, 1 points, 1 comments]