ArticleChaos, solitons, and fractals2020
Time series forecasting of Covid-19 using deep learning models: India-USA comparative case study.
Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers, 3 of them syntheses that pooled it.
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Who cites it
81 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Machine Learning Used in Communicable Disease Control: A Scoping Review.Public health reviews · 2026Pooled it
- The COVID-19 epidemic analysis and diagnosis using deep learning: A systematic literature review and future directions.Computers in biology and medicine · 2022Pooled it
- Artificial Intelligence for COVID-19: A Systematic Review.Frontiers in medicine · 2021Pooled it
- Enhancing COVID-19 Forecasting Accuracy in Malaysia Using a Hybrid ARIMA-LSTM Model With Exogenous Variables: A Time-Series Predictive Study.Health science reports · 2026Article
- Spatio-temporal epidemic forecasting with graph-based transformer.International journal of health geographics · 2026Article
- Interpreting epidemiological surveillance data: a modelling study based on Pune city.Scientific reports · 2025Article
- Time series forecasting of Valley fever infection in Maricopa County, AZ using LSTM.Lancet regional health. Americas · 2025Article
- Hybrid ARIMA-LSTM for COVID-19 forecasting: a comparative AI modeling study.PeerJ. Computer science · 2025Article
- A prediction approach to COVID-19 time series with LSTM integrated attention mechanism and transfer learning.BMC medical research methodology · 2024Article
- A novel ensemble ARIMA-LSTM approach for evaluating COVID-19 cases and future outbreak preparedness.Health care science · 2024Article
- Frequency-specific dual-attention based adversarial network for blood oxygen level-dependent time series prediction.Human brain mapping · 2024Article
- A New Auto-Regressive Multi-Variable Modified Auto-Encoder for Multivariate Time-Series Prediction: A Case Study with Application to COVID-19 Pandemics.International journal of environmental research and public health · 2024Article
- AI-powered COVID-19 forecasting: a comprehensive comparison of advanced deep learning methods.Osong public health and research perspectives · 2024Article
- Tracing the COVID-19 spread pattern in India through a GIS-based spatio-temporal analysis of interconnected clusters.Scientific reports · 2024Article
- Deep learning in public health: Comparative predictive models for COVID-19 case forecasting.PloS one · 2024Article
- A novel bidirectional LSTM deep learning approach for COVID-19 forecasting.Scientific reports · 2023Article
- Article
- Machine Learning Algorithms Associate Case Numbers with SARS-CoV-2 Variants Rather Than with Impactful Mutations.Viruses · 2023Article
- Analysis and Prediction of COVID-19 Multivariate Data Using Deep Ensemble Learning Methods.International journal of environmental research and public health · 2023Article
- Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach.EBioMedicine · 2023Article
21 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Covid-19 is a highly contagious virus which almost freezes the world along with its economy. Its ability of human-to-human and surface-to-human transmission turns the world into catastrophic phase. In this study, our aim is to predict the future conditions of novel Coronavirus to recede its impact. We have proposed deep learning based comparative analysis of Covid-19 cases in India and USA. The datasets of confirmed and death cases of Covid-19 are taken into consideration. The recurrent neural network (RNN) based variants of long short term memory (LSTM) such as Stacked LSTM, Bi-directional LSTM and Convolutional LSTM are used to design the proposed methodology and forecast the Covid-19 cases for one month ahead. Convolution LSTM outperformed the other two models and predicts the Covid-19 cases with high accuracy and very less error for all four datasets of both countries. Upward/downward trend of forecasted Covid-19 cases are also visualized graphically, which would be helpful for researchers and policy makers to mitigate the mortality and morbidity rate by streaming the Covid-19 into right direction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.