ArticleBiomimetics (Basel, Switzerland)2023
An Optimized Model Based on Deep Learning and Gated Recurrent Unit for COVID-19 Death Prediction.
Article in Biomimetics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 20 citations in OpenAlex.
- Integrating Clinical Priorities into the Technical Validation of Machine Learning Classifiers: A Generalizable Framework Demonstrated on Opioid Misuse Screening.Journal of clinical medicine · 2026Article
- Prediction of death in burn patients infected with antibiotic-resistant Staphylococcus aureus using machine learning based techniques.BMC infectious diseases · 2026Article
- AI-Based Prediction of Gene Expression in Single-Cell and Multiscale Genomics and Transcriptomics.International journal of molecular sciences · 2026Review
- Generative artificial intelligence in public health: a framework for governance and systemic integration.Frontiers in medicine · 2026Review
- A Hybrid Convolutional, Mamba and Spiking Neural Network Architecture Search for Seizure Prediction.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- COVID-19 mortality and nutrition through predictive modeling and optimization based on grid search.Scientific reports · 2025Article
- Improved CKD classification based on explainable artificial intelligence with extra trees and BBFS.Scientific reports · 2025Article
- Breast cancer classification based on hybrid CNN with LSTM model.Scientific reports · 2025Article
- Enhancing heart disease classification based on greylag goose optimization algorithm and long short-term memory.Scientific reports · 2025Article
- An enhanced adaptive dynamic metaheuristic optimization algorithm for rainfall prediction depends on long short-term memory.PloS one · 2025Article
- Investigating the Key Trends in Applying Artificial Intelligence to Health Technologies: A Scoping Review.PloS one · 2025Article
- Orthopedic disease classification based on breadth-first search algorithm.Scientific reports · 2024Article
- Innovation through Artificial Intelligence in Triage Systems for Resource Optimization in Future Pandemics.Biomimetics (Basel, Switzerland) · 2024Article
- Impact of the COVID-19 pandemic and COVID vaccination campaign on imaging case volumes and medicolegal aspects.Frontiers in health services · 2024Article
Corrections and comments
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Authors and funding
11 authors at 8 institutions in 7 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 epidemic poses a worldwide threat that transcends provincial, philosophical, spiritual, radical, social, and educational borders. By using a connected network, a healthcare system with the Internet of Things (IoT) functionality can effectively monitor COVID-19 cases. IoT helps a COVID-19 patient recognize symptoms and receive better therapy more quickly. A critical component in measuring, evaluating, and diagnosing the risk of infection is artificial intelligence (AI). It can be used to anticipate cases and forecast the alternate incidences number, retrieved instances, and injuries. In the context of COVID-19, IoT technologies are employed in specific patient monitoring and diagnosing processes to reduce COVID-19 exposure to others. This work uses an Indian dataset to create an enhanced convolutional neural network with a gated recurrent unit (CNN-GRU) model for COVID-19 death prediction via IoT. The data were also subjected to data normalization and data imputation. The 4692 cases and eight characteristics in the dataset were utilized in this research. The performance of the CNN-GRU model for COVID-19 death prediction was assessed using five evaluation metrics, including median absolute error (MedAE), mean absolute error (MAE), root mean squared error (RMSE), mean square error (MSE), and coefficient of determination (R
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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.