AIMC Topic: Epidemics

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Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.

Journal of medical Internet research
BACKGROUND: In megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious diseases. Existing prediction and early warning models for influenza and other acute respiratory inf...

Optimal control by deep learning techniques and its applications on epidemic models.

Journal of mathematical biology
We represent the optimal control functions by neural networks and solve optimal control problems by deep learning techniques. Adjoint sensitivity analysis is applied to train the neural networks embedded in differential equations. This method can not...

A Hybrid Model for Coronavirus Disease 2019 Forecasting Based on Ensemble Empirical Mode Decomposition and Deep Learning.

International journal of environmental research and public health
The novel coronavirus pneumonia that began to spread in 2019 is still raging and has placed a burden on medical systems and governments in various countries. For policymaking and medical resource decisions, a good prediction model is necessary to mon...

Network Sentiment Analysis of College Students in Different Epidemic Stages Based on Text Clustering.

Journal of environmental and public health
In order to analyze the evolution trend of public opinion in emergencies and explore its evolution law, this paper constructs a network sentiment analysis model based on text clustering, where the emotion analysis part is based on the pretraining BER...

Optimization: Molecular Communication Networks for Viral Disease Analysis Using Deep Leaning Autoencoder.

Computational and mathematical methods in medicine
Developing new treatments for emerging infectious diseases in infectious and noninfectious diseases has attracted a particular attention. The emergence of viral diseases is expected to accelerate; these data indicate the need for a proactive approach...

Spatial Prediction of COVID-19 in China Based on Machine Learning Algorithms and Geographically Weighted Regression.

Computational and mathematical methods in medicine
COVID-19 has swept through the world since December 2019 and caused a large number of patients and deaths. Spatial prediction on the spread of the epidemic is greatly important for disease control and management. In this study, we predicted the cumul...

Toward a systematic conflict resolution framework for ontologies.

Journal of biomedical semantics
BACKGROUND: The ontology authoring step in ontology development involves having to make choices about what subject domain knowledge to include. This may concern sorting out ontological differences and making choices between conflicting axioms due to ...

The Infectious Disease Ontology in the age of COVID-19.

Journal of biomedical semantics
BACKGROUND: Effective response to public health emergencies, such as we are now experiencing with COVID-19, requires data sharing across multiple disciplines and data systems. Ontologies offer a powerful data sharing tool, and this holds especially f...

Predicting malaria epidemics in Burkina Faso with machine learning.

PloS one
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 ...

Assessing the Outbreak Risk of Epidemics Using Fuzzy Evidential Reasoning.

Risk analysis : an official publication of the Society for Risk Analysis
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...