The Differentiated Creative search (DCS): Leveraging Differentiated knowledge-acquisition and Creative realism to address complex optimization problems

P Duankhan, K Sunat, S Chiewchanwattana… - Expert Systems with …, 2024 - Elsevier
This article introduces differentiated creative search (DCS), a groundbreaking optimization
algorithm that revolutionizes traditional decision-making systems in complex environments …

A novel lightweight CNN for chest X-ray-based lung disease identification on heterogeneous embedded system

T Sanida, M Dasygenis - Applied Intelligence, 2024 - Springer
The global spread of epidemic lung diseases, including COVID-19, underscores the need
for efficient diagnostic methods. Addressing this, we developed and tested a computer …

Machine learning models for predicting hospitalization and mortality risks of COVID-19 patients

WD de Holanda, LC e Silva, ÁACC Sobrinho - Expert Systems with …, 2024 - Elsevier
Abstract Even though the World Health Organization declared the end of the pandemic,
COVID-19 is still considered an endemic disease, affecting many people worldwide. As a …

Detection of SARS-CoV-2 virus using lightweight convolutional neural networks

A Kumar, BK Chaurasia - Wireless Personal Communications, 2024 - Springer
A highly contagious illness caused by the SARS-CoV-2 virus pandemic is proven to wreak
havoc on people's health and well-being all over the globe. Severe Acute Respiratory …

[HTML][HTML] Detecting health misinformation: A comparative analysis of machine learning and graph convolutional networks in classification tasks

B Khemani, S Patil, K Kotecha, D Vora - MethodsX, 2024 - Elsevier
In the digital age, the proliferation of health-related information online has heightened the
risk of misinformation, posing substantial threats to public well-being. This research …

COVID-19 IgG antibodies detection based on CNN-BiLSTM algorithm combined with fiber-optic dataset

MJA Alathari, Y Al Mashhadany, AAA Bakar… - Journal of Virological …, 2024 - Elsevier
The urgent need for efficient and accurate automated screening tools for COVID-19
detection has led to research efforts exploring various approaches. In this study, we present …

COVID-19 studies involving machine learning methods: a bibliometric study

AB Eden, AB Kayi, MG Erdem, M Demirci - Medicine, 2023 - journals.lww.com
Background: Machine learning (ML) and artificial intelligence (AI) techniques are gaining
popularity as effective tools for coronavirus disease of 2019 (COVID-19) research. These …

Using the textual content of radiological reports to detect emerging diseases: a proof-of-concept study of COVID-19

A Crombé, JC Lecomte, M Seux, N Banaste… - Journal of Imaging …, 2024 - Springer
Abstract Changes in the content of radiological reports at population level could detect
emerging diseases. Herein, we developed a method to quantify similarities in consecutive …

CGS‐Net: A classification‐guided framework for automated infection segmentation of COVID‐19 from CT images

W Zhou, J Wang, Y Wang, Z Liu… - International Journal of …, 2024 - Wiley Online Library
Automated segmentation of lung lesions in CT images of COVID‐19 based on deep learning
holds great potential for comprehending the advancement of the disease and establishing …

[PDF][PDF] Bridging Pandemics and Pixels: a Comprehensive Bibliometric Analysis of Deep Learning Applications in Covid-19 Detection

MZC Daud, FWA Zaiki, MZC Azemin - Journal of Information …, 2024 - irep.iium.edu.my
The world has been significantly impacted by the global pandemic of COVID-19, leading
researchers to explore various methods for detecting the virus. Deep learning (DL) …