Browse State-of-the-Art › Epidemiology
Epidemiology
106 papers with code · 0 benchmarks · 1 dataset archive 2025-07-28
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
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
30 shown of 106 papers with code (425 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
-
13 Mar 2020 3 repositories listedIn addition, our method incorporates a summary network trained to embed the observed data into maximally informative summary statistics.
-
21 May 2023 2 repositories listed Syntology ran 7 of 7 samples · 0 unverified · 7 pointer-only (licence)To enhance the learning of each step, an elaborated spatio-temporal co-attention module is proposed to capture the interdependence between the event time and space adaptively.
-
9 Dec 2022 2 repositories listedDiscrete stochastic processes are prevalent in natural systems, with applications in physics, biochemistry, epidemiology, sociology, and finance.
-
9 Jun 2021 2 repositories listed Syntology ran 3 of 8 samples · 5 unverified · 7 pointer-only (licence)Modeling complex spatiotemporal dynamical systems, such as the reaction-diffusion processes, have largely relied on partial differential equations (PDEs).
-
9 Oct 2020 2 repositories listedEpidemiologists model the dynamics of epidemics in order to propose control strategies based on pharmaceutical and non-pharmaceutical interventions (contact limitation, lock down, vaccination, etc).
-
14 May 2020 2 repositories listedThe COVID-19 pandemic has highlighted the importance of in-silico epidemiological modelling in predicting the dynamics of infectious diseases to inform health policy and decision makers about suitable prevention and…
-
22 Jun 2019 2 repositories listed Syntology ran 0 of 5 samples · 5 unverifiedOur model represents each task as the linear combination of the realizations of latent processes that are integrated at a different scale per task.
-
21 Feb 2019 2 repositories listedCorrespondence analysis (CA) is a multivariate statistical tool used to visualize and interpret data dependencies.
-
26 Feb 2018 2 repositories listedThe first, critical, task for these applications is classifying whether a personal health event was mentioned, which we call the (PHM) problem.
-
14 Jul 2025 1 repository listedStochastic Petri Nets (SPNs) are an increasingly popular tool of choice for modeling discrete-event dynamics in areas such as epidemiology and systems biology, yet their parameter estimation remains challenging in…
-
21 May 2025 1 repository listedWe generalize earlier results on a single data source and derive conditions for applying pruning and clustering in the case of multiple data sources.
-
13 May 2025 1 repository listedA major challenge with this task is the absence of structural-temporal coupling information, which decreases the ability of the representation to distinguish anomalies from normal instances.
-
3 Apr 2025 1 repository listedThere has been interest in the interactions between infectious disease dynamics and behaviour for most of the history of mathematical epidemiology.
-
5 Mar 2025 1 repository listedWe find that an increased proportion of cases moving through a ``mild recovery route" -- which can occur with different host susceptibility or increased public health intervention -- leads to a model structure in which…
-
26 Feb 2025 1 repository listedAccurate calibration of stochastic agent-based models (ABMs) in epidemiology is crucial to make them useful in public health policy decisions and interventions.
-
11 Feb 2025 1 repository listedStochastic reaction networks (SRNs) model stochastic effects for various applications, including intracellular chemical or biological processes and epidemiology.
-
9 Feb 2025 1 repository listedAnd we show that existing methods for constructing confidence (or credible) intervals for associations fail to provide nominal coverage in the face of model misspecification and distribution shift - despite both being…
-
6 Feb 2025 1 repository listedFurther, we show how such created datasets can be used by benchmarking several machine learning models on the epidemiological dataset.
-
20 Jan 2025 1 repository listedDespite the growing availability of clinical and demographic data, predictive models for lung metastasis in HCC remain limited in scope and clinical applicability.
-
20 Nov 2024 1 repository listedFurthermore, we provide a theoretical result demonstrating that it is instead the mean recovery time, which is the mean of the inverse 1/γ of the recovery rate that is critical in deciding whether herd immunity is…
-
17 Nov 2024 1 repository listedThis assumption simplifies the mathematical description of the population considerably, enabling continuum-limit descriptions to be derived and used in model analysis and fitting.
-
7 Nov 2024 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)TrajGPT integrates the spatial and temporal models in a transformer architecture through a Bayesian probability model that ensures that the gaps in a visit sequence are filled in a spatiotemporally consistent manner.
-
5 Nov 2024 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)Amortized simulation-based inference (SBI) methods train neural networks on simulated data to perform Bayesian inference.
-
3 Nov 2024 1 repository listedThis important result seems to be little known outside of ME; even in ME, it has not been made clear before that the method gets sometimes the right answer, even though the conditions of the NGM theorem are not all…
-
17 Oct 2024 1 repository listedThe second relies on sparse identification of nonlinear dynamics (SINDy), a popular method for discovering governing equations, which we use for the first time as a general tool for explainability.
-
10 Oct 2024 1 repository listedWe introduce a neural architecture finetuned for the task of scenario context generation: The relevant location and time of an event or entity mentioned in text.
-
10 Oct 2024 1 repository listed Syntology ran 5 of 5 samples · 0 unverified · 5 pointer-only (licence)Simulation-based inference (SBI) is the preferred framework for estimating parameters of intractable models in science and engineering.
-
3 Oct 2024 1 repository listed Syntology ran 5 of 8 samples · 3 unverified · 8 pointer-only (licence)Multivariate Time Series (MTS) forecasting is a fundamental task with numerous real-world applications, such as transportation, climate, and epidemiology.
-
28 Sep 2024 1 repository listed Syntology ran 1 of 1 samples · 0 unverifiedTo accommodate both the global coherence of epidemic trends and the local nuances of epidemic transmission patterns, we build a cross-attention approach to fuse the most meaningful information for forecasting.
-
2 Sep 2024 1 repository listedTo address this issue, we developed a new method called Sparse Identification of Nonlinear Dynamical Systems from Graph-structured data (SINDyG), which incorporates the network structure into sparse regression to…
Syntology lines on 8 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections