AI Medical Compendium Topic:
SARS-CoV-2

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Potent multi-target natural inhibitors against SARS-CoV-2 from medicinal plants of the Himalaya: a discovery from hybrid machine learning, chemoinformatics, and simulation assisted screening.

Journal of biomolecular structure & dynamics
The emergence and immune evasion ability of SARS-CoV-2 Omicron strains, mainly BA.5.2 and BF.7 and other variants of concern have raised global apprehensions. With this context, the discovery of multitarget inhibitors may be proven more comprehensive...

A robust deep learning workflow to predict CD8 + T-cell epitopes.

Genome medicine
BACKGROUND: T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, which has sparked interest in the development of various T-cell-focus...

Coot-Lion optimized deep learning algorithm for COVID-19 point mutation rate prediction using genome sequences.

Computer methods in biomechanics and biomedical engineering
In this study, a deep quantum neural network (DQNN) based on the Lion-based Coot algorithm (LBCA-based Deep QNN) is employed to predict COVID-19. Here, the genome sequences are subjected to feature extraction. The fusion of features is performed usin...

Using machine learning to estimate health spillover effects.

The European journal of health economics : HEPAC : health economics in prevention and care
We develop a nonparametric model to study health spillover effects of policy interventions. We use double/debiased machine learning to estimate the model using data from 74 hospitals in Rio de Janeiro, Brazil, and examine cross-patient spillover effe...

Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron.

PloS one
Topic modelling with innovative deep learning methods has gained interest for a wide range of applications that includes COVID-19. It can provide, psychological, social and cultural insights for understanding human behaviour in extreme events such as...

Deep-learning-enabled protein-protein interaction analysis for prediction of SARS-CoV-2 infectivity and variant evolution.

Nature medicine
Host-pathogen interactions and pathogen evolution are underpinned by protein-protein interactions between viral and host proteins. An understanding of how viral variants affect protein-protein binding is important for predicting viral-host interactio...

SVM-RFE enabled feature selection with DMN based centroid update model for incremental data clustering using COVID-19.

Computer methods in biomechanics and biomedical engineering
This research introduces an efficacious model for incremental data clustering using Entropy weighted-Gradient Namib Beetle Mayfly Algorithm (NBMA). Here, feature selection is done based upon support vector machine recursive feature elimination (SVM-R...

Novel fuzzy deep learning approach for automated detection of useful COVID-19 tweets.

Artificial intelligence in medicine
Coronavirus (COVID-19) is a newly discovered viral disease from the SARS-CoV-2 family. This has caused a moral panic resulting in the spread of informative and uninformative information about COVID-19 and its effects. Twitter is a popular social medi...

Harnessing the power of AI: Advanced deep learning models optimization for accurate SARS-CoV-2 forecasting.

PloS one
The pandemic has significantly affected many countries including the USA, UK, Asia, the Middle East and Africa region, and many other countries. Similarly, it has substantially affected Malaysia, making it crucial to develop efficient and precise for...

A computationally-inexpensive strategy in CT image data augmentation for robust deep learning classification in the early stages of an outbreak.

Biomedical physics & engineering express
Coronavirus disease 2019 (COVID-19) has spread globally for over three years, and chest computed tomography (CT) has been used to diagnose COVID-19 and identify lung damage in COVID-19 patients. Given its widespread, CT will remain a common diagnosti...