On the adoption of modern technologies to fight the COVID-19 pandemic: a technical synthesis of latest developments

A Majeed, X Zhang - COVID, 2023 - mdpi.com
In the ongoing COVID-19 pandemic, digital technologies have played a vital role to minimize
the spread of COVID-19, and to control its pitfalls for the general public. Without such …

[HTML][HTML] Utilizing CNN-LSTM techniques for the enhancement of medical systems

A Rayan, AS Alaerjan, S Alanazi, AI Taloba… - Alexandria Engineering …, 2023 - Elsevier
COVID-19 is one of the most chronic and serious infections of recent years due to its
worldwide spread. Determining who was genuinely affected when the disease spreads …

The public health contribution of sentiment analysis of Monkeypox tweets to detect polarities using the CNN-LSTM model

O Iparraguirre-Villanueva, A Alvarez-Risco… - Vaccines, 2023 - mdpi.com
Monkeypox is a rare disease caused by the monkeypox virus. This disease was considered
eradicated in 1980 and was believed to affect rodents and not humans. However, recent …

Comparison of tree-based model with deep learning model in predicting effluent pH and concentration by capacitive deionization

Z Ullah, N Yoon, BK Tarus, S Park, M Son - Desalination, 2023 - Elsevier
Capacitive deionization (CDI) is an emerging technique for water treatment and
electroadsorption processes (ie, brackish water desalination). Various numerical modeling …

Interpretable temporal attention network for COVID-19 forecasting

B Zhou, G Yang, Z Shi, S Ma - Applied soft computing, 2022 - Elsevier
The worldwide outbreak of coronavirus disease 2019 (COVID-19) has triggered an
unprecedented global health and economic crisis. Early and accurate forecasts of COVID-19 …

Deep Learning Algorithm for COVID‐19 Classification Using Chest X‐Ray Images

S VJ - Computational and Mathematical Methods in Medicine, 2021 - Wiley Online Library
Early diagnosis of the harmful severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐
2), along with clinical expertise, allows governments to break the transition chain and flatten …

A bidirectional long short-term memory model algorithm for predicting COVID-19 in gulf countries

THH Aldhyani, H Alkahtani - Life, 2021 - mdpi.com
Accurate prediction models have become the first goal for aiding pandemic-related
decisions. Modeling and predicting the number of new active cases and deaths are …

Hybrid learning-oriented approaches for predicting Covid-19 time series data: A comparative analytical study

S Mehrmolaei, M Savargiv, MR Keyvanpour - Engineering Applications of …, 2023 - Elsevier
Using medical science alongside time series data analysis can be given a strong tool to
develop efficient decision support systems in Corona pandemic. In this regard, many hybrid …

Prediction of Omicron Virus Using Combined Extended Convolutional and Recurrent Neural Networks Technique on CT‐Scan Images

AK Gupta, A Srinivasulu, KK Hiran… - Interdisciplinary …, 2022 - Wiley Online Library
COVID‐19 has sparked a global pandemic, with a variety of inflamed instances and deaths
increasing on an everyday basis. Researchers are actively increasing and improving distinct …

Hybrid ensemble deep learning-based approach for time series energy prediction

PP Phyo, YC Byun - Symmetry, 2021 - mdpi.com
The energy manufacturers are required to produce an accurate amount of energy by
meeting the energy requirements at the end-user side. Consequently, energy prediction …