Epidemiology

70 papers with code • 0 benchmarks • 1 datasets

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

Datasets


Latest papers with no code

Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer

no code yet • 5 Apr 2024

We propose Deep Longitudinal Targeted Minimum Loss-based Estimation (Deep LTMLE), a novel approach to estimate the counterfactual mean of outcome under dynamic treatment policies in longitudinal problem settings.

TransformerLSR: Attentive Joint Model of Longitudinal Data, Survival, and Recurrent Events with Concurrent Latent Structure

no code yet • 4 Apr 2024

However, current methods only address joint modeling of longitudinal measurements at regularly-spaced observation times and survival events, neglecting recurrent events.

TS-CausalNN: Learning Temporal Causal Relations from Non-linear Non-stationary Time Series Data

no code yet • 1 Apr 2024

The growing availability and importance of time series data across various domains, including environmental science, epidemiology, and economics, has led to an increasing need for time-series causal discovery methods that can identify the intricate relationships in the non-stationary, non-linear, and often noisy real world data.

Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis

no code yet • 25 Mar 2024

Fortunately, in this work, we found that the causal order from $X$ to its child $Y$ is identifiable if $X$ is a root vertex and has at least two directed paths to $Y$, or the ancestor of $X$ with the most directed path to $X$ has a directed path to $Y$ without passing $X$.

What makes a small-world network? Leveraging machine learning for the robust prediction and classification of networks

no code yet • 20 Mar 2024

The ability to simulate realistic networks based on empirical data is an important task across scientific disciplines, from epidemiology to computer science.

Public Goods Games in Disease Evolution and Spread

no code yet • 27 Feb 2024

We also posit that applications of evolutionary game theory to decision-making in cancer, such as interactions between a clinician and a tumour, can learn from the PGGs studied in epidemiology, where cooperative behaviours such as quarantine and vaccination compliance have been more thoroughly investigated.

Information Theory Unification of Epidemiological and Population Dynamics

no code yet • 26 Feb 2024

Concretely, we propose a simple form of the metric for which we can analytically solve the dynamics of the system that well approximates the time evolution of various established models in epidemiology and population dynamics, thus providing a unifying framework.

Ethnic Disparities of Female Infiltrating Duct and Lobular Breast Cancer Survival by Cancer Stage: Findings From SEER 2006-2010

no code yet • 16 Feb 2024

We found significant associations between racial groups and ages with significant differences in age between Blacks and Whites, and Whites and Others.

Unlocking Unlabeled Data: Ensemble Learning with the Hui- Walter Paradigm for Performance Estimation in Online and Static Settings

no code yet • 17 Jan 2024

In the realm of machine learning and statistical modeling, practitioners often work under the assumption of accessible, static, labeled data for evaluation and training.

Kernel Density Estimation for Multiclass Quantification

no code yet • 31 Dec 2023

Several disciplines, like the social sciences, epidemiology, sentiment analysis, or market research, are interested in knowing the distribution of the classes in a population rather than the individual labels of the members thereof.