Cargando…
Data-Driven Deep Learning Neural Networks for Predicting the Number of Individuals Infected by COVID-19 Omicron Variant
Infectious disease epidemics are challenging for medical and public health practitioners. They require prompt treatment, but it is challenging to recognize and define epidemics in real time. Knowing the prediction of an infectious disease epidemic can evaluate and prevent the disease’s impact. Mathe...
Autores principales: | Oluwasakin, Ebenezer O., Khaliq, Abdul Q. M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594457/ https://www.ncbi.nlm.nih.gov/pubmed/37873886 http://dx.doi.org/10.3390/epidemiologia4040037 |
Ejemplares similares
-
Deep-Data-Driven Neural Networks for COVID-19 Vaccine Efficacy
por: Torku, Thomas K., et al.
Publicado: (2021) -
Data-Driven Deep-Learning Algorithm for Asymptomatic COVID-19 Model with Varying Mitigation Measures and Transmission Rate
por: Olumoyin, K. D., et al.
Publicado: (2021) -
Reproduction Number of the Omicron Variant Triples That of the Delta Variant
por: Du, Zhanwei, et al.
Publicado: (2022) -
Vector Auto-Regressive Deep Neural Network: A Data-Driven Deep Learning-Based Directed Functional Connectivity Estimation Toolbox
por: Okuno, Takuto, et al.
Publicado: (2021) -
Visual number sense in untrained deep neural networks
por: Kim, Gwangsu, et al.
Publicado: (2021)