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Digital Epidemiology
Computational social science has had a profound impact on the study of health and disease, mainly by providing new data sources for all of the...
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Gender and the h-index in epidemiology
Gender-Based differences in h- indices across fields, including psychology, social work, and the biomedical sciences have been reported. These...
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Spreader-Centric Fake News Mitigation Framework Based on Epidemiology
Computational models for the detection and prevention of false information spreading (popularly called fake news) has gained a lot of attention over...
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Identification of Environmental Epidemiology Through Advanced Remote Sensing Based on NDVI
Advanced Remote Sensing (ARS) is a new scientific subject that combines high-performance computers and innovative spatial science techniques to...
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Risk Stratification of Breast Cancer Patients: Integrating Epidemiology, Risk Factors, and Prognostic Markers for Sustainable Development
The classification of breast cancer risk into high and low categories is essential for individualized treatment planning and enhanced patient...
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Computational Epidemiology From Disease Transmission Modeling to Vaccination Decision Making
This book provides a comprehensive introduction to computational epidemiology, highlighting its major methodological paradigms throughout the...
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Paradigms in Epidemiology
This chapter provides an overview of infectious disease epidemiology, highlighting some of the major methodological paradigm shifts throughout the...
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Supervised Machine Learning Models for Prediction of COVID-19 Infection using Epidemiology Dataset
COVID-19 or 2019-nCoV is no longer pandemic but rather endemic, with more than 651,247 people around world having lost their lives after contracting...
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Automatically Protecting Network Communities by Malware Epidemiology
Malware epidemiology, specifically the modelling and simulation of malware propagation, has been theorised to improve malware outbreak preparedness...
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Welcome to the Era of Systems Epidemiology
This chapter offers a fresh outlook on the latest methodological paradigm in infectious disease epidemiology, i.e., systems epidemiology....
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A Non-autonom SIR Model in Epidemiology
With the outbreak of COVID-19, the modelling of epidemic spread has once again become highly important. This paper introduces an epidemic spreading...
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Ontological Representation of Causal Relations for a Deep Understanding of Associations Between Variables in Epidemiology
Understanding statistical results is crucial in order to spread right conclusions. In observational studies, statistical results are often reported...
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GLIMPSE: a glioblastoma prognostication model using ensemble learning—a surveillance, epidemiology, and end results study
PurposeGlioblastoma is one of the most common and aggressive brain tumors in the world with a poor prognosis. A glioblastoma prognostication model...
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Prediction of the Impact of the End of year Festivities on the Local Epidemiology of COVID-19 Using Agent-Based Simulation with Hidden Markov Models
Towards the end of 2020, as people changed their usual behavior due to end of year festivities, increasing the frequency of meetings and the number...
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Applications of Quantification
This chapter provides the motivation for what is to come in the rest of the book by describing the applications that quantification has been put at,...
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The exciting potential and daunting challenge of using GPS human-mobility data for epidemic modeling
Large-scale GPS location datasets hold immense potential for measuring human mobility and interpersonal contact, both of which are essential for...
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Computational tools and databases at the forefront to study geographic and genomic distribution of SARS-CoV-2 variants
In human history, crippling viral pandemics have occurred many times and recently Coronavirus-19 (COVID-19) disease caused by novel severe acute...
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Branching Process Simulator in R
We developed a set of software functionalities in R for simulation of branching processes. Originally it was designed for simulating the branching...
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SOPHIE: Viral Outbreak Investigation and Transmission History Reconstruction in a Joint Phylogenetic and Network Theory Framework
Reconstruction of transmission networks from viral genomes sampled from infected individuals is a major computational problem of genomic...
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Cad2graph: Automated Extraction of Spatial Graphs from Architectural Drawings
A significant obstacle to spatial epidemiology in healthcare facilities is the absence of computationally amenable maps of the underlying space....