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Epidemiology

Epidemiology is a scientific discipline that provides reliable knowledge for clinical medicine focusing on prevention, diagnosis and treatment of diseases. Research in Epidemiology aims at characterizing risk factors for the outbreak of diseases and at evaluating the efficiency of certain treatment strategies, e.g., to compare a new treatment with an established gold standard. This research is strongly hypothesis-driven and statistical analysis is the major tool for epidemiologists so far. Correlations between genetic factors, environmental factors, life style-related parameters, age and diseases are analyzed.

Source: Visual Analytics of Image-Centric Cohort Studies in Epidemiology

Papers

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Showing 1–50 of 425 papers

TitleStatusHype
A Simple Approximate Bayesian Inference Neural Surrogate for Stochastic Petri Net ModelsCode0
Six Decades Post-Discovery of Taylor's Power Law: From Ecological and Statistical Universality, Through Prime Number Distributions and Tipping-Point Signals, to Heterogeneity and Stability of Complex Networks—0
Improving wastewater-based epidemiology through strategic placement of samplers—0
A note on metapopulation models—0
Mamba Integrated with Physics Principles Masters Long-term Chaotic System ForecastingCode0
Symbolic Foundation Regressor on Complex Networks—0
Are Statistical Methods Obsolete in the Era of Deep Learning?—0
Bayesian ensemble learning for predicting health outcomes of multipollutant mixtures—0
Clustering and Pruning in Causal Data FusionCode0
Structural-Temporal Coupling Anomaly Detection with Dynamic Graph TransformerCode0
Mathematical epidemiology of infectious diseases: an ongoing challenge—0
New insights into population dynamics from the continuous McKendrick model—0
A Hamiltonian Higher-Order Elasticity Framework for Dynamic Diagnostics(2HOED)—0
The two-clock problem in population dynamics—0
Simulating biochemical reactions: The Linear Noise Approximation can capture non-linear dynamics—0
Continuous and discrete compartmental models for infectious disease—0
Deep spatio-temporal point processes: Advances and new directions—0
A Behaviour and Disease Model of Testing and IsolationCode0
Identifying Macro Causal Effects in C-DMGs—0
Group centrality in optimal and suboptimal vaccination for epidemic models in contact networks—0
Dynamic Graph Structure Estimation for Learning Multivariate Point Process using Spiking Neural Networks—0
Topological Properties of the Effective Reproduction Number in an Heterogeneous SIS Model—0
Coupling plankton and cholera dynamics: insights into outbreak prediction and practical disease management—0
Bayesian Semi-Parametric Spatial Dispersed Count Model for Precipitation Analysis—0
Structural and Practical Identifiability of Phenomenological Growth Models for Epidemic Forecasting—0
Optimal virulence strategies in epidemiological models with asymptomatic transmissionCode0
Primer C-VAE: An interpretable deep learning primer design method to detect emerging virus variants—0
Advancing calibration for stochastic agent-based models in epidemiology with Stein variational inference and Gaussian process surrogatesCode0
Yesil o1 Pro: Evidence-Based AI Model for Health and Benchmarking in Clinical Decision Support—0
Filtered Markovian Projection: Dimensionality Reduction in Filtering for Stochastic Reaction NetworksCode0
Smooth Sailing: Lipschitz-Driven Uncertainty Quantification for Spatial AssociationCode0
Synthetic Datasets for Machine Learning on Spatio-Temporal Graphs using PDEsCode0
An SIRS-model considering waning efficiency and periodic re-vaccination—0
Redefining Influenza Transmission Seasonality Using the Novel Seasonality Index—0
Prediction of Lung Metastasis from Hepatocellular Carcinoma using the SEER DatabaseCode0
Recovering Unobserved Network Links from Aggregated Relational Data: Discussions on Bayesian Latent Surface Modeling and Penalized Regression—0
SEANN: A Domain-Informed Neural Network for Epidemiological Insights—0
Modelling Activity Scheduling Behaviour with Deep Generative Machine Learning—0
Quantum-enhanced causal discovery for a small number of samples—0
Predicting high dengue incidence in municipalities of Brazil using path signatures—0
Discovering maximally consistent distribution of causal tournaments with Large Language Models—0
WaveGNN: Modeling Irregular Multivariate Time Series for Accurate Predictions—0
Gearing Gaussian process modeling and sequential design towards stochastic simulators—0
Nature versus nurture in galaxy formation: the effect of environment on star formation with causal machine learning—0
Digital Epidemiology: Leveraging Social Media for Insight into Epilepsy and Mental Health—0
Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data—0
Epidemiology-informed Graph Neural Network for Heterogeneity-aware Epidemic Forecasting—0
Epidemiology-informed Network for Robust Rumor Detection—0
The impact of recovery rate heterogeneity in achieving herd immunityCode0
Random walk models in the life sciences: including births, deaths and local interactionsCode0
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