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Epidemiology

19 papers with code · Medical

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

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Greatest papers with code

Simulation-Based Inference for Global Health Decisions

14 May 2020mrc-ide/covid-sim

The 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 containment strategies.

BAYESIAN INFERENCE EPIDEMIOLOGY

Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks

NeurIPS 2018 sjblim/rmsn_nips_2018

Electronic health records provide a rich source of data for machine learning methods to learn dynamic treatment responses over time.

EPIDEMIOLOGY

Data-driven Identification of Number of Unreported Cases for COVID-19: Bounds and Limitations

3 Jun 2020scc-usc/ReCOVER-COVID-19

A critical factor that can hinder accurate long-term forecasts, is the number of unreported/asymptomatic cases.

EPIDEMIOLOGY

BayesFlow: Learning complex stochastic models with invertible neural networks

13 Mar 2020stefanradev93/cINN

In addition, our method incorporates a summary network trained to embed the observed data into maximally informative summary statistics.

BAYESIAN INFERENCE EPIDEMIOLOGY

Total Variation Regularization for Compartmental Epidemic Models with Time-Varying Dynamics

1 Apr 2020WenjieZ/2019-nCoV

Compartmental epidemic models are among the most popular ones in epidemiology.

EPIDEMIOLOGY

Multi-task Learning for Aggregated Data using Gaussian Processes

NeurIPS 2019 frb-yousefi/multitask-gp

Our model represents each task as the linear combination of the realizations of latent processes that are integrated at a different scale per task.

AIR POLLUTION PREDICTION EPIDEMIOLOGY GAUSSIAN PROCESSES MULTI-TASK LEARNING

Parameter elimination in particle Gibbs sampling

NeurIPS 2019 uu-sml/neurips2019-parameter-elimination

Bayesian inference in state-space models is challenging due to high-dimensional state trajectories.

EPIDEMIOLOGY PROBABILISTIC PROGRAMMING

Uncertainty-aware generative models for inferring document class prevalence

EMNLP 2018 slanglab/doc_prevalence

Prevalence estimation is the task of inferring the relative frequency of classes of unlabeled examples in a group{---}for example, the proportion of a document collection with positive sentiment.

BAYESIAN INFERENCE EPIDEMIOLOGY

Spatio-Temporal Data Mining: A Survey of Problems and Methods

13 Nov 2017devbas/ovassistant-alpha

Large volumes of spatio-temporal data are increasingly collected and studied in diverse domains including, climate science, social sciences, neuroscience, epidemiology, transportation, mobile health, and Earth sciences.

ANOMALY DETECTION CLUSTERING EPIDEMIOLOGY