AIMC Topic: SARS-CoV-2

Clear Filters Showing 421 to 430 of 1734 articles

Dual-branch Transformer for semi-supervised medical image segmentation.

Journal of applied clinical medical physics
PURPOSE: In recent years, the use of deep learning for medical image segmentation has become a popular trend, but its development also faces some challenges. Firstly, due to the specialized nature of medical data, precise annotation is time-consuming...

Comparative analysis of feature selection techniques for COVID-19 dataset.

Scientific reports
In the context of early disease detection, machine learning (ML) has emerged as a vital tool. Feature selection (FS) algorithms play a crucial role in ensuring the accuracy of predictive models by identifying the most influential variables. This stud...

Admission blood tests predicting survival of SARS-CoV-2 infected patients: a practical implementation of graph convolution network in imbalance dataset.

BMC infectious diseases
BACKGROUND: Predicting an individual's risk of death from COVID-19 is essential for planning and optimising resources. However, since the real-world mortality rate is relatively low, particularly in places like Hong Kong, this makes building an accur...

CMM: A CNN-MLP Model for COVID-19 Lesion Segmentation and Severity Grading.

IEEE/ACM transactions on computational biology and bioinformatics
In this paper, a CNN-MLP model (CMM) is proposed for COVID-19 lesion segmentation and severity grading in CT images. The CMM starts by lung segmentation using UNet, and then segmenting the lesion from the lung region using a multi-scale deep supervis...

Global Research on Pandemics or Epidemics and Mental Health: A Natural Language Processing Study.

Journal of epidemiology and global health
BACKGROUND: The global research on pandemics or epidemics and mental health has been growing exponentially recently, which cannot be integrated through traditional systematic review. Our study aims to systematically synthesize the evidence using natu...

Artificial Intelligence and Blockchain Enabled Smart Healthcare System for Monitoring and Detection of COVID-19 in Biomedical Images.

IEEE/ACM transactions on computational biology and bioinformatics
Millions of individuals around the world have been impacted by the ongoing coronavirus outbreak, known as the COVID-19 pandemic. Blockchain, Artificial Intelligence (AI), and other cutting-edge digital and innovative technologies have all offered pro...

Integrated CNN and Federated Learning for COVID-19 Detection on Chest X-Ray Images.

IEEE/ACM transactions on computational biology and bioinformatics
Currently, Coronavirus Disease 2019 (COVID-19) is still endangering world health and safety and deep learning (DL) is expected to be the most powerful method for efficient detection of COVID-19. However, patients' privacy concerns prohibit data shari...

Cooperating Graph Neural Networks With Deep Reinforcement Learning for Vaccine Prioritization.

IEEE journal of biomedical and health informatics
This study explores the vaccine prioritization strategy to reduce the overall burden of the pandemic when the supply is limited. Existing vaccine distribution methods focus on macro-level or simplified micro-level assuming homogeneous behavior within...

Navigating artificial intelligence in care homes: Competing stakeholder views of trust and logics of care.

Social science & medicine (1982)
The COVID-19 pandemic shed light on systemic issues plaguing care (nursing) homes, from staff shortages to substandard healthcare. Artificial Intelligence (AI) technologies, including robots and chatbots, have been proposed as solutions to such issue...

Identifying psychological predictors of SARS-CoV-2 vaccination: A machine learning study.

Vaccine
BACKGROUND: Major barriers to addressing SARS-CoV-2 vaccine hesitancy include limited knowledge of what causes delay/refusal of SARS-CoV-2 vaccination and limited ability to predict who will remain unvaccinated over significant time periods despite v...