ArticleProcess safety and environmental protection : transactions of the Institution of Chemical Engineers, Part B2021
Deep learning-based forecasting model for COVID-19 outbreak in Saudi Arabia.
Article in Process safety and environmental protection : transactions of the Institution of Chemical Engineers, Part B, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning Used in Communicable Disease Control: A Scoping Review.Public health reviews · 2026Pooled it
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- Forecasting the spread of COVID-19 based on policy, vaccination, and Omicron data.Scientific reports · 2024Article
- AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods.Osong public health and research perspectives · 2024Article
- Deep learning in public health: Comparative predictive models for COVID-19 case forecasting.PloS one · 2024Article
- Transfer-recursive-ensemble learning for multi-day COVID-19 prediction in India using recurrent neural networks.Scientific reports · 2023Article
- A novel prediction model based on decomposition-integration and error correction for COVID-19 daily confirmed and death cases.Computers in biology and medicine · 2023Article
- Data driven contagion risk management in low-income countries using machine learning applications with COVID-19 in South Asia.Scientific reports · 2023Article
- Green fluorometric strategy for simultaneous determination of the antihypertensive drug telmisartan (A tentative therapeutic for COVID-19) with Nebivolol in human plasma.Scientific reports · 2023Article
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- Data analytics and knowledge management approach for COVID-19 prediction and control.International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management · 2023Article
- Deep learning framework for epidemiological forecasting: A study on COVID-19 cases and deaths in the Amazon state of Pará, Brazil.PloS one · 2023Article
- Harnessing the power of AI: Advanced deep learning models optimization for accurate SARS-CoV-2 forecasting.PloS one · 2023Article
- Machine Learning and Deep Learning Based Time Series Prediction and Forecasting of Ten Nations' COVID-19 Pandemic.SN computer science · 2023Article
- Deep learning for Covid-19 forecasting: State-of-the-art review.Neurocomputing · 2022Article
- Forecasting admissions in psychiatric hospitals before and during Covid-19: a retrospective study with routine data.Scientific reports · 2022Article
- Weather Conditions and COVID-19 Cases: Insights from the GCC Countries.Intelligent systems with applications · 2022Article
- A data-driven hybrid ensemble AI model for COVID-19 infection forecast using multiple neural networks and reinforced learning.Computers in biology and medicine · 2022Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19 outbreak has become a global pandemic that affected more than 200 countries. Predicting the epidemiological behavior of this outbreak has a vital role to prevent its spreading. In this study, long short-term memory (LSTM) network as a robust deep learning model is proposed to forecast the number of total confirmed cases, total recovered cases, and total deaths in Saudi Arabia. The model was trained using the official reported data. The optimal values of the model's parameters that maximize the forecasting accuracy were determined. The forecasting accuracy of the model was assessed using seven statistical assessment criteria, namely, root mean square error (RMSE), coefficient of determination (R
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