AIMC Topic: COVID-19

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CoTrFuse: a novel framework by fusing CNN and transformer for medical image segmentation.

Physics in medicine and biology
Medical image segmentation is a crucial and intricate process in medical image processing and analysis. With the advancements in artificial intelligence, deep learning techniques have been widely used in recent years for medical image segmentation. O...

Development and validation of a hybrid deep learning-machine learning approach for severity assessment of COVID-19 and other pneumonias.

Scientific reports
The Coronavirus Disease 2019 (COVID-19) is transitioning into the endemic phase. Nonetheless, it is crucial to remain mindful that pandemics related to infectious respiratory diseases (IRDs) can emerge unpredictably. Therefore, we aimed to develop an...

Exploring intelligent hospital management mode based on artificial intelligence.

Frontiers in public health
OBJECTIVE: To address the challenges posed by the COVID-19 pandemic, our hospital developed an intelligent hospital management mode specifically tailored to COVID-19 patients.

GENERA: A Combined Genetic/Deep-Learning Algorithm for Multiobjective Target-Oriented De Novo Design.

Journal of chemical information and modeling
This study introduces a new de novo design algorithm called that combines the capabilities of a deep-learning algorithm for automated drug-like analogue design, called , with a genetic algorithm for generating molecules with desired target-oriented ...

The accuracy of artificial intelligence in predicting COVID-19 patient mortality: a systematic review and meta-analysis.

BMC medical informatics and decision making
BACKGROUND: The purpose of this paper was to systematically evaluate the application value of artificial intelligence in predicting mortality among COVID-19 patients.

Remote Blood Oxygen Estimation From Videos Using Neural Networks.

IEEE journal of biomedical and health informatics
Peripheral blood oxygen saturation (SpO ) is an essential indicator of respiratory functionality and received increasing attention during the COVID-19 pandemic. Clinical findings show that COVID-19 patients can have significantly low SpO before any ...

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...

Training certified detectives to track down the intrinsic shortcuts in COVID-19 chest x-ray data sets.

Scientific reports
Deep learning faces a significant challenge wherein the trained models often underperform when used with external test data sets. This issue has been attributed to spurious correlations between irrelevant features in the input data and corresponding ...

ChatGPT: unlocking the potential of Artifical Intelligence in COVID-19 monitoring and prediction.

Panminerva medica
BACKGROUND: The COVID-19 pandemic has had an unprecedent impact of everyday life with deleterious consequences on global health, economics, and society. Thus, accurate and timely information is critical for monitoring its spread and mitigating its im...

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...