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The importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic
The COVID-19 pandemic has brought about valuable insights regarding models, data, and
experiments. In this narrative review, we summarised the existing literature on these three …
experiments. In this narrative review, we summarised the existing literature on these three …
PETLFC: Parallel ensemble transfer learning based framework for COVID-19 differentiation and prediction using deep convolutional neural network models
Despite a worldwide research involvement in the global COVID-19 pandemic, the research
community is still struggling to develop reliable and faster prediction mechanisms for this …
community is still struggling to develop reliable and faster prediction mechanisms for this …
A Boosted Evolutionary Neural Architecture Search for Time Series Forecasting with Application to South African COVID-19 Cases.
In recent years, there has been an increase in studies on time-series forecasting for the
future occurrence of disease incidents. Improvements in deep learning approaches offer …
future occurrence of disease incidents. Improvements in deep learning approaches offer …
FlightKoopman: Deep Koopman for Multi-Dimensional Flight Trajectory Prediction
J Lu, J Jiang, Y Bai, W Dai, W Zhang - International Journal of …, 2025 - World Scientific
Multi-dimensional Flight Trajectory Prediction (MFTP) in Flight Operations Quality
Assessment (FOQA) refers to the estimation of flight status at the future time, accurate …
Assessment (FOQA) refers to the estimation of flight status at the future time, accurate …
IoT-Cloud-Centric Smart Healthcare Monitoring System for Heart Disease Prediction Using a Gated-Controlled Deep Unfolding Network with Crayfish Optimization
The rising incidence of heart disease requires effective and robust prediction algorithms,
especially in Internet of Things (IoT)-cloud-based smart healthcare frameworks. This study …
especially in Internet of Things (IoT)-cloud-based smart healthcare frameworks. This study …
Interpretable deep learning and transfer learning-based spatial-temporal modeling for vaccines demand prediction
L Altarawneh - 2023 - search.proquest.com
This study proposes prediction models to identify vaccination rates and anticipate vaccine
demand in develo** countries or regions, with a focus on the COVID-19 vaccination. The …
demand in develo** countries or regions, with a focus on the COVID-19 vaccination. The …
Hybrid and Ensemble Artificial Intelligence-Based Time Series Techniques with Applications in Power and Health Sectors
SO Akinola - 2024 - search.proquest.com
In the current fourth industrial revolution (4IR), governments and businesses increasingly
leverage large datasets and artificial intelligence (AI) to glean insights for competitive …
leverage large datasets and artificial intelligence (AI) to glean insights for competitive …