AI Medical Compendium Topic:
SARS-CoV-2

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Multi-objective optimization determines when, which and how to fuse deep networks: An application to predict COVID-19 outcomes.

Computers in biology and medicine
The COVID-19 pandemic has caused millions of cases and deaths and the AI-related scientific community, after being involved with detecting COVID-19 signs in medical images, has been now directing the efforts towards the development of methods that ca...

Socioexposomics of COVID-19 across New Jersey: a comparison of geostatistical and machine learning approaches.

Journal of exposure science & environmental epidemiology
BACKGROUND: Disparities in adverse COVID-19 health outcomes have been associated with multiple social and environmental stressors. However, research is needed to evaluate the consistency and efficiency of methods for studying these associations at lo...

Deep Learning-Based Bioactive Therapeutic Peptide Generation and Screening.

Journal of chemical information and modeling
Many bioactive peptides demonstrated therapeutic effects over complicated diseases, such as antiviral, antibacterial, anticancer, . It is possible to generate a large number of potentially bioactive peptides using deep learning in a manner analogous ...

Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations.

JAMA network open
IMPORTANCE: Earlier detection of emerging novel SARS-COV-2 variants is important for public health surveillance of potential viral threats and for earlier prevention research. Artificial intelligence may facilitate early detection of SARS-CoV2 emergi...

PneuNet: deep learning for COVID-19 pneumonia diagnosis on chest X-ray image analysis using Vision Transformer.

Medical & biological engineering & computing
A long-standing challenge in pneumonia diagnosis is recognizing the pathological lung texture, especially the ground-glass appearance pathological texture. One main difficulty lies in precisely extracting and recognizing the pathological features. Th...

A survey of machine learning-based methods for COVID-19 medical image analysis.

Medical & biological engineering & computing
The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected after only 30 months since the first occurrences of the disease in December 2019. Hence, rapid and accu...

CNN-RNN Network Integration for the Diagnosis of COVID-19 Using Chest X-ray and CT Images.

Sensors (Basel, Switzerland)
The 2019 coronavirus disease (COVID-19) has rapidly spread across the globe. It is crucial to identify positive cases as rapidly as humanely possible to provide appropriate treatment for patients and prevent the pandemic from spreading further. Both ...

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank.

Genetic epidemiology
Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic de...

Classification of COVID-19 from community-acquired pneumonia: Boosting the performance with capsule network and maximum intensity projection image of CT scans.

Computers in biology and medicine
BACKGROUND: The coronavirus disease 2019 (COVID-19) and community-acquired pneumonia (CAP) present a high degree of similarity in chest computed tomography (CT) images. Therefore, a procedure for accurately and automatically distinguishing between th...

Benchmarking of Machine Learning classifiers on plasma proteomic for COVID-19 severity prediction through interpretable artificial intelligence.

Artificial intelligence in medicine
The SARS-CoV-2 pandemic highlighted the need for software tools that could facilitate patient triage regarding potential disease severity or even death. In this article, an ensemble of Machine Learning (ML) algorithms is evaluated in terms of predict...