AIMC Topic: SARS-CoV-2

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Bibliometric Insights Into the Infodemic: Global Research Trends and Policy Responses: Quantitative Research.

JMIR medical informatics
BACKGROUND: Amidst the COVID-19 pandemic, the proliferation of misinformation on social media, termed the "infodemic," has complicated global health responses.

FragOPT: An ML-Driven Computational Workflow for Rational Fragments Optimization Toward Lead Compounds.

Journal of chemical information and modeling
Advances in machine learning (ML) offer significant potential to accelerate drug discovery. Although mathematical modeling and ML have become crucial in predicting drug-target interactions and properties, the complexity of chemical space and the "bla...

Using machine learning models to predict vaccine hesitancy: a showcase of COVID-19 vaccine hesitancy in rural populations during the pandemic.

Vaccine
Understanding vaccine hesitancy is a critical public health challenge, yet traditional statistical methods often fail to capture the complex drivers behind it. This study uses COVID-19 vaccine hesitancy in a rural population as a case study to demons...

Ionizable Lipid Nanoparticles for mRNA Delivery: Internal Self-Assembled Inverse Mesophase Structure and Endosomal Escape.

Accounts of chemical research
ConspectusThe clinical use of mRNA COVID-19 vaccines developed by Moderna and Pfizer-BioNTech has highlighted the critical role of ionizable lipid nanoparticles (LNPs) in the efficient loading, intracellular delivery, and cytoplasmic release of mRNAs...

Transfer learning with fuzzy decision support for multi-class lung disease classification: performance analysis of pre-trained CNN models.

Scientific reports
Accurate and efficient classification of lung diseases from medical images remains a significant challenge in computer-aided diagnosis systems. This research presents a novel approach integrating transfer learning techniques with fuzzy decision suppo...

Analytical and machine learning approaches identify a sea star steroid with promising activity for COVID-19 therapeutic development.

Scientific reports
The pressing demand for safe and efficient COVID-19 treatments has intensified interest in Natural products, especially those derived from marine organisms. In this study, a bioactive steroidal compound, 5α-cholesta-9(11)-en-3β,20β-diol, was successf...

Rapid reagent free COVID19 detection using MEMS based FTIR spectroscopy and machine learning in NIR and MIR regions.

Scientific reports
This study presents rapid, reagent-free detection of COVID-19 using miniaturized MEMS-based Fourier-transform infrared (FTIR) spectrometers integrated with machine learning models. Two portable spectrometers analyze 363 nasopharyngeal swab samples st...

Manifold-constrained nucleus-level denoising diffusion model for structure-based drug design.

Proceedings of the National Academy of Sciences of the United States of America
AI models have shown great potential in structure-based drug design, generating ligands with high binding affinities. However, existing models have often overlooked a crucial physical prior: Atoms must maintain a minimum pairwise distance to avoid at...

COVID-19 mortality and nutrition through predictive modeling and optimization based on grid search.

Scientific reports
Since 2019, humanity has been suffering from the negative impact of COVID-19, and the virus did not stop in its usual state but began to pivot to become more harmful until it reached its form now, which is the omicron variant. Therefore, in an attemp...

Machine learning models to identify significant factors of panic buying situation.

Scientific reports
In panic-buying situations, individuals suddenly purchase excessive quantities of goods, leading to a massive crisis of essential goods in the market. As a result, many consumers cannot access the required products, creating an unstable societal situ...