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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 251–300 of 425 papers

TitleStatusHype
Prediction of Prognosis and Survival of Patients with Gastric Cancer by Weighted Improved Random Forest Model—0
Data-driven deep learning algorithms for time-varying infection rates of COVID-19 and mitigation measures—0
Defining the lead time of wastewater-based epidemiology for COVID-19—0
Impact of climate change on West Nile virus distribution in South America—0
Spatiotemporal Data Mining: A Survey on Challenges and Open Problems—0
MOAI: A methodology for evaluating the impact of indoor airflow in the transmission of COVID-19—0
Multi-Source Causal Inference Using Control Variates—0
Use of mathematical modelling to assess respiratory syncytial virus epidemiology and interventions: A literature review—0
Outcome-guided Sparse K-means for Disease Subtype Discovery via Integrating Phenotypic Data with High-dimensional Transcriptomic DataCode0
Data-Driven Methods for Present and Future Pandemics: Monitoring, Modelling and Managing—0
Exact epidemic models from a tensor product formulation—0
Learning Epidemiology by Doing: The Empirical Implications of a Spatial-SIR Model with Behavioral Responses—0
The EpiBench Platform to Propel AI/ML-based Epidemic Forecasting: A Prototype Demonstration Reaching Human Expert-level Performance—0
The field theoretical ABC of epidemic dynamics—0
Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions—0
Deep Learning applications for COVID-19—0
A deep learning modeling framework to capture mixing patterns in reactive-transport systems—0
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
Neural Spatio-Temporal Point ProcessesCode1
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
EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological ModelsCode1
OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in GermanyCode1
Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment EffectsCode1
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
A Data-Driven Control-Theoretic Paradigm for Pandemic Mitigation with Application to Covid-19—0
Estimating Structural Target Functions using Machine Learning and Influence FunctionsCode0
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
Automated Stitching of Coral Reef Images and Extraction of Features for Damselfish Shoaling Behavior Analysis—0
From the Black-Karasinski to the Verhulst model to accommodate the unconventional Fed's policy—0
Rule-based epidemic models—0
A Novel Epidemiological Approach to Geographically Mapping Population Dry Eye Disease in the United States through Google Trends—0
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