AI Medical Compendium Topic:
SARS-CoV-2

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Machine and deep learning methods for clinical outcome prediction based on physiological data of COVID-19 patients: a scoping review.

International journal of medical informatics
INTRODUCTION: Since the beginning of the COVID-19 pandemic, numerous machine and deep learning (MDL) methods have been proposed in the literature to analyze patient physiological data. The objective of this review is to summarize various aspects of t...

Identifying the Interaction Between Tuberculosis and SARS-CoV-2 Infections via Bioinformatics Analysis and Machine Learning.

Biochemical genetics
The number of patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 is still increasing. In the case of COVID-19 and tuberculosis (TB), the presence of one disease affects the infectious status of the other. Meanwhile, coin...

Experimental validation of immunogenic SARS-CoV-2 T cell epitopes identified by artificial intelligence.

Frontiers in immunology
During the COVID-19 pandemic we utilized an AI-driven T cell epitope prediction tool, the NEC Immune Profiler (NIP) to scrutinize and predict regions of T cell immunogenicity (hotspots) from the entire SARS-CoV-2 viral proteome. These immunogenic reg...

Simple and Multiplexed Detection of Nucleic Acid Targets Based on Fluorescent Ring Patterns and Deep Learning Analysis.

ACS applied materials & interfaces
Simple diagnostic tests for nucleic acid targets can provide great advantages for applications such as rapid pathogen detection. Here, we developed a membrane assay for multiplexed detection of nucleic acid targets based on the visualization of two-d...

Deep learning, 3D ultrastructural analysis reveals quantitative differences in platelet and organelle packing in COVID-19/SARSCoV2 patient-derived platelets.

Platelets
Platelets contribute to COVID-19 clinical manifestations, of which microclotting in the pulmonary vasculature has been a prominent symptom. To investigate the potential diagnostic contributions of overall platelet morphology and their α-granules and ...

Generation of focused drug molecule library using recurrent neural network.

Journal of molecular modeling
CONTEXT: With the wide application of deep learning in drug research and development, de novo molecular design methods based on recurrent neural network (RNN) have strong advantages in drug molecule generation. The RNN model can be used to learn the ...

Application of Machine Learning Models to Biomedical and Information System Signals From Critically Ill Adults.

Chest
BACKGROUND: Machine learning (ML)-derived notifications for impending episodes of hemodynamic instability and respiratory failure events are interesting because they can alert physicians in time to intervene before these complications occur.

Screening COVID-19 by Swaasa AI platform using cough sounds: a cross-sectional study.

Scientific reports
The Advent of Artificial Intelligence (AI) has led to the use of auditory data for detecting various diseases, including COVID-19. SARS-CoV-2 infection has claimed more than six million lives to date and therefore, needs a robust screening technique ...

Blue-emitting SiO-coated Si-doped ZnSeS quantum dots conjugated aptamer-molecular beacon as an electrochemical and metal-enhanced fluorescence biosensor for SARS-CoV-2 spike protein.

Analytica chimica acta
The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which was first reported in early January 2020, continues to devastate the worlds public health system. Herein, we report on the development of a novel metal-enhanced fluore...

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...