AIMC Topic: Epidemics

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Predicting malaria epidemics in Burkina Faso with machine learning.

PloS one Jun 18, 2021
Accurately forecasting the case rate of malaria would enable key decision makers to intervene months before the onset of any outbreak, potentially saving lives. Until now, methods that forecast malaria have involved complicated numerical simulations ...
Humans Machine Learning Male Infant Malaria Algorithms Databases, Factual Female Burkina Faso Epidemics
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Assessing the Outbreak Risk of Epidemics Using Fuzzy Evidential Reasoning.

Risk analysis : an official publication of the Society for Risk Analysis Apr 17, 2021
Epidemic diseases (EDs) present a significant but challenging risk endangering public health, evidenced by the outbreak of COVID-19. Compared to other risks affecting public health such as flooding, EDs attract little attention in terms of risk asses...
Male Middle Aged Risk Assessment Risk Factors Adult Sensitivity and Specificity Public Health Humans Epidemics Disease Outbreaks Fuzzy Logic Software Public Health Administration China Principal Component Analysis COVID-19 SARS-CoV-2
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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...
Basic Reproduction Number Computer Simulation Epidemics Deep Learning Humans Models, Statistical
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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...
Population Models, Statistical Bayes Theorem Epidemics Humans Neural Networks, Computer Communicable Diseases Computer Simulation
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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...
Pneumonia, Viral Coronavirus Coronavirus Infections Epidemics Betacoronavirus SARS-CoV-2 Deep Learning Humans United States Pandemics COVID-19 Research Design
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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...
Patient Readmission Epidemics Deep Learning Big Data Diabetes Mellitus Humans Neural Networks, Computer Algorithms
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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...
Europe Models, Statistical Aircraft Algorithms Humans Epidemics Forecasting Machine Learning Travel ROC Curve Dengue
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COVID-19 Epidemic: Possibility of Artificial Intelligence in Infection Control and Prevention.

Journal of epidemiology Jun 6, 2020
Epidemics COVID-19 Global Health Pneumonia, Viral Coronavirus Infections Humans Artificial Intelligence Pandemics
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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...
Epidemiological Monitoring Humans Neural Networks, Computer Tuberculosis Germany Epidemics Machine Learning Forecasting Diabetes Mellitus
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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...
Epidemics Humans Disease Outbreaks Machine Learning China COVID-19 Models, Theoretical Forecasting
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