AIMC Topic: Epidemics

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A deep learning based surrogate model for the parameter identification problem in probabilistic cellular automaton epidemic models.

Computer methods and programs in biomedicine Apr 1, 2021
BACKGROUND AND OBJECTIVE: an accurate estimation of the epidemiological model coefficients helps understand the basic principles of disease spreading. Some studies showed that dozens of hours are needed to simulate the traditional probabilistic cellu...
Models, Statistical Basic Reproduction Number Epidemics Humans Computer Simulation Deep Learning
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Network inference from population-level observation of epidemics.

Scientific reports Nov 2, 2020
Using the continuous-time susceptible-infected-susceptible (SIS) model on networks, we investigate the problem of inferring the class of the underlying network when epidemic data is only available at population-level (i.e., the number of infected ind...
Bayes Theorem Epidemics Population Computer Simulation Models, Statistical Humans Neural Networks, Computer Communicable Diseases
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Dynamics and Development of the COVID-19 Epidemic in the United States: A Compartmental Model Enhanced With Deep Learning Techniques.

Journal of medical Internet research Aug 21, 2020
BACKGROUND: Compartmental models dominate epidemic modeling. Transmission parameters between compartments are typically estimated through stochastic parameterization processes that depends on detailed statistics of transmission characteristics, which...
Pandemics COVID-19 Research Design Humans Betacoronavirus Pneumonia, Viral Coronavirus United States Coronavirus Infections Epidemics SARS-CoV-2 Deep Learning
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Research of Epidemic Big Data Based on Improved Deep Convolutional Neural Network.

Computational and mathematical methods in medicine Jul 22, 2020
In recent years, with the acceleration of the aging process and the aggravation of life pressure, the proportion of chronic epidemics has gradually increased. A large amount of medical data will be generated during the hospitalization of diabetics. I...
Diabetes Mellitus Algorithms Humans Epidemics Patient Readmission Deep Learning Neural Networks, Computer Big Data
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Predicting dengue importation into Europe, using machine learning and model-agnostic methods.

Scientific reports Jun 16, 2020
The geographical spread of dengue is a global public health concern. This is largely mediated by the importation of dengue from endemic to non-endemic areas via the increasing connectivity of the global air transport network. The dynamic nature and i...
Aircraft Epidemics Travel Dengue ROC Curve Europe Models, Statistical Algorithms Forecasting Humans Machine Learning
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COVID-19 Epidemic: Possibility of Artificial Intelligence in Infection Control and Prevention.

Journal of epidemiology Jun 6, 2020
COVID-19 Global Health Coronavirus Infections Artificial Intelligence Pandemics Epidemics Pneumonia, Viral Humans
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Forecasting tuberculosis using diabetes-related google trends data.

Pathogens and global health May 26, 2020
Online activity-based data can be used to aid infectious disease forecasting. Our aim was to exploit the converging nature of the tuberculosis (TB) and diabetes epidemics to forecast TB case numbers. Thus, we extended TB prediction models based on tr...
Tuberculosis Machine Learning Epidemiological Monitoring Germany Humans Forecasting Epidemics Diabetes Mellitus Neural Networks, Computer
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Modeling the trend of coronavirus disease 2019 and restoration of operational capability of metropolitan medical service in China: a machine learning and mathematical model-based analysis.

Global health research and policy May 6, 2020
BACKGROUND: To contain the outbreak of coronavirus disease 2019 (COVID-19) in China, many unprecedented intervention measures are adopted by the government. However, these measures may interfere in the normal medical service. We sought to model the t...
Humans Disease Outbreaks Epidemics Machine Learning China COVID-19 Models, Theoretical Forecasting
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True epidemic growth construction through harmonic analysis.

Journal of theoretical biology Mar 12, 2020
In this paper, we have proposed a two-phase procedure (combining discrete graphs and wavelets) for constructing true epidemic growth. In the first phase, a graph-theory-based approach was developed to update partial data available and in the second p...
Machine Learning Models, Biological Epidemics
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Risk perception and behavioral change during epidemics: Comparing models of individual and collective learning.

PloS one Jan 6, 2020
Modern societies are exposed to a myriad of risks ranging from disease to natural hazards and technological disruptions. Exploring how the awareness of risk spreads and how it triggers a diffusion of coping strategies is prominent in the research age...
Social Learning Cholera Computer Simulation Adaptation, Psychological Decision Making Humans Social Behavior Risk Factors Epidemics Machine Learning Interpersonal Relations Models, Theoretical
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