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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 276–300 of 425 papers

TitleStatusHype
Diagnosis/Prognosis of COVID-19 Images: Challenges, Opportunities, and Applications—0
Hardware-accelerated Simulation-based Inference of Stochastic Epidemiology Models for COVID-19Code0
Handling uncertainty using features from pathology: opportunities in primary care data for developing high risk cancer survival methods—0
Accelerating Simulation-based Inference with Emerging AI HardwareCode0
Inference of Stochastic Dynamical Systems from Cross-Sectional Population Data—0
Methodology for Mining, Discovering and Analyzing Semantic Human Mobility Behaviors—0
Overview of the Fifth Social Media Mining for Health Applications (#SMM4H) Shared Tasks at COLING 2020—0
Supervised Machine Learning Models for Prediction of COVID-19 Infection using Epidemiology Dataset—0
The k-statistics approach to epidemiology—0
Phase transition in Kermack-McKendrick Model of Epidemic: Effects of Additional Nonlinearity and Introduction of Medicated Immunity—0
Mobile Human Ad Hoc Networks: A Communication Engineering Viewpoint on Interhuman Airborne Pathogen TransmissionCode0
Algorithmic Reduction of Biological Networks With Multiple Time Scales—0
Dynamic causal modelling of immune heterogeneity—0
Disease control as an optimization problemCode0
Tracking disease outbreaks from sparse data with Bayesian inference—0
Solvable delay model for epidemic spreading: the case of Covid-19 in Italy—0
Referenced Thermodynamic Integration for Bayesian Model Selection: Application to COVID-19 Model SelectionCode0
Unfolding selection to infer individual risk heterogeneity for optimising disease forecasts and policy development—0
Learning Dynamical Systems with Side InformationCode0
Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications—0
Estimating Structural Target Functions using Machine Learning and Influence FunctionsCode0
A Data-Driven Control-Theoretic Paradigm for Pandemic Mitigation with Application to Covid-19—0
COVID-19 Twitter Dataset with Latent Topics, Sentiments and Emotions AttributesCode0
Quantitative clarification of key questions about COVID-19 epidemiology—0
Bridging the COVID-19 Data and the Epidemiological Model using Time Varying Parameter SIRD Model—0
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