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COVID-19

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Comparing machine learning screening approaches using clinical data and cytokine profiles for COVID-19 in resource-limited and resource-abundant settings.

Scientific reports
Accurate screening of COVID-19 infection status for symptomatic patients is a critical public health task. Although molecular and antigen tests now exist for COVID-19, in resource-limited settings, screening tests are often not available. Furthermore...

A real-world test of artificial intelligence infiltration of a university examinations system: A "Turing Test" case study.

PloS one
The recent rise in artificial intelligence systems, such as ChatGPT, poses a fundamental problem for the educational sector. In universities and schools, many forms of assessment, such as coursework, are completed without invigilation. Therefore, stu...

Predictive modelling of stress, anxiety and depression: A network analysis and machine learning study.

The British journal of clinical psychology
OBJECTIVE: This study assessed predictors of stress, anxiety and depression during the COVID-19 pandemic using a large number of demographic, COVID-19 context and psychological variables.

A retrospective study of deep learning generalization across two centers and multiple models of X-ray devices using COVID-19 chest-X rays.

Scientific reports
Generalization of deep learning (DL) algorithms is critical for the secure implementation of computer-aided diagnosis systems in clinical practice. However, broad generalization remains to be a challenge in machine learning. This research aims to ide...

Machine learning-based QSAR and LB-PaCS-MD guided design of SARS-CoV-2 main protease inhibitors.

Bioorganic & medicinal chemistry letters
The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (M). The ligand-bi...

Leveraging advances in data-driven deep learning methods for hybrid epidemic modeling.

Epidemics
Mathematical modeling of epidemic dynamics is crucial to understand its underlying mechanisms, quantify important parameters, and make predictions that facilitate more informed decision-making. There are three major types of models: mechanistic model...

Molybdenum Disulfide-Assisted Spontaneous Formation of Multistacked Gold Nanoparticles for Deep Learning-Integrated Surface-Enhanced Raman Scattering.

ACS nano
Several fabrication methods have been developed for label-free detection in various fields. However, fabricating high-density and highly ordered nanoscale architectures by using soluble processes remains a challenge. Herein, we report a biosensing pl...

Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker.

Nature aging
Short-term mortality risk, which is indicative of individual frailty, serves as a marker for aging. Previous age clocks focused on predicting either chronological age or longer-term mortality. Aging clocks predicting short-term mortality are lacking ...

A tree-based explainable AI model for early detection of Covid-19 using physiological data.

BMC medical informatics and decision making
With the outbreak of COVID-19 in 2020, countries worldwide faced significant concerns and challenges. Various studies have emerged utilizing Artificial Intelligence (AI) and Data Science techniques for disease detection. Although COVID-19 cases have ...

Determination of prognostic markers for COVID-19 disease severity using routine blood tests and machine learning.

Anais da Academia Brasileira de Ciencias
The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients' care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This ...