AIMC Topic: COVID-19

Clear Filters Showing 891 to 900 of 2468 articles

Research on the Application of Artificial Intelligence in Public Health Management: Leveraging Artificial Intelligence to Improve COVID-19 CT Image Diagnosis.

International journal of environmental research and public health
Since the start of 2020, the outbreak of the Coronavirus disease (COVID-19) has been a global public health emergency, and it has caused unprecedented economic and social disaster. In order to improve the diagnosis efficiency of COVID-19 patients, a ...

Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review.

Computers in biology and medicine
The growing and aging of the world population have driven the shortage of medical resources in recent years, especially during the COVID-19 pandemic. Fortunately, the rapid development of robotics and artificial intelligence technologies help to adap...

Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era.

IEEE reviews in biomedical engineering
At the beginning of the COVID-19 pandemic, there was significant hype about the potential impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or surveillance. However, AI tools have not yet been widely success...

Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review.

IEEE reviews in biomedical engineering
Despite the myriad peer-reviewed papers demonstrating novel Artificial Intelligence (AI)-based solutions to COVID-19 challenges during the pandemic, few have made a significant clinical impact, especially in diagnosis and disease precision staging. O...

Identification of Asymptomatic COVID-19 Patients on Chest CT Images Using Transformer-Based or Convolutional Neural Network-Based Deep Learning Models.

Journal of digital imaging
Novel coronavirus disease 2019 (COVID-19) has rapidly spread throughout the world; however, it is difficult for clinicians to make early diagnoses. This study is to evaluate the feasibility of using deep learning (DL) models to identify asymptomatic ...

Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment.

Sensors (Basel, Switzerland)
Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the real world domain. Artificial intelligence, the driving force of the current technological revolutio...

LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases.

Sensors (Basel, Switzerland)
This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This framework is termed optimized DenseNet201 for lung diseases (LDDNet). The pro...

Explainable Machine Learning Model to Predict COVID-19 Severity Among Older Adults in the Province of Quebec.

Annals of family medicine
Context: Patients over the age of 65 years are more likely to experience higher severity and mortality rates than other populations from COVID-19. Clinicians need assistance in supporting their decisions regarding the management of these patients. Ar...

Smartwatch Sensors with Deep Learning to Predict the Purchase Intentions of Online Shoppers.

Sensors (Basel, Switzerland)
In the past decade, the scale of e-commerce has continued to grow. With the outbreak of the COVID-19 epidemic, brick-and-mortar businesses have been actively developing online channels where precision marketing has become the focus. This study propos...