AIMC Topic: Epidemics
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Hyper-parameter tuned deep learning approach for effective human monkeypox disease detection.
Scientific reports
Sep 23, 2023
Human monkeypox is a very unusual virus that can devastate society. Early identification and diagnosis are essential to treat and manage an illness effectively. Human monkeypox disease detection using deep learning models has attracted increasing att...
Application of image processing and transfer learning for the detection of rust disease.
Scientific reports
Mar 29, 2023
Plant diseases introduce significant yield and quality losses to the food production industry, worldwide. Early identification of an epidemic could lead to more effective management of the disease and potentially reduce yield loss and limit excessive...
Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.
Journal of medical Internet research
Feb 13, 2023
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
Jan 25, 2023
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
Dec 29, 2022
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
Sep 27, 2022
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
Dec 13, 2021
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
Oct 13, 2021
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
Aug 9, 2021
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
Jul 18, 2021
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...
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