AIMC Topic: COVID-19

Clear Filters Showing 771 to 780 of 2468 articles

Harnessing artificial intelligence in the post-COVID-19 era: A global health imperative.

Tropical doctor
Despite the World Health Organization's declaration that the COVID-19 global emergency has ended, the threat of future pandemics remains a significant concern. This paper highlights the potential role of Artificial Intelligence (AI) in strengthening ...

Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations.

Computers in biology and medicine
The COVID-19 pandemic has necessitated the development of reliable diagnostic methods for accurately detecting the novel coronavirus and its variants. Deep learning (DL) techniques have shown promising potential as screening tools for COVID-19 detect...

Deep learning for deterioration prediction of COVID-19 patients based on time-series of three vital signs.

Scientific reports
Unrecognized deterioration of COVID-19 patients can lead to high morbidity and mortality. Most existing deterioration prediction models require a large number of clinical information, typically collected in hospital settings, such as medical images o...

Artificial intelligence-driven prediction of COVID-19-related hospitalization and death: a systematic review.

Frontiers in public health
AIM: To perform a systematic review on the use of Artificial Intelligence (AI) techniques for predicting COVID-19 hospitalization and mortality using primary and secondary data sources.

The Rise of AI: How Artificial Intelligence is Revolutionizing Infectious Disease Control.

Annals of biomedical engineering
Artificial Intelligence (AI) has proven to be an effective tool in predicting, detecting, and mitigating the spread of infectious diseases, especially during the COVID-19 pandemic. The technology is increasingly playing a role in preventing future he...

Pathological changes or technical artefacts? The problem of the heterogenous databases in COVID-19 CXR image analysis.

Computer methods and programs in biomedicine
BACKGROUND: When the COVID-19 pandemic commenced in 2020, scientists assisted medical specialists with diagnostic algorithm development. One scientific research area related to COVID-19 diagnosis was medical imaging and its potential to support molec...

Modification of a Conventional Deep Learning Model to Classify Simulated Breathing Patterns: A Step toward Real-Time Monitoring of Patients with Respiratory Infectious Diseases.

Sensors (Basel, Switzerland)
The emergence of the global coronavirus pandemic in 2019 (COVID-19 disease) created a need for remote methods to detect and continuously monitor patients with infectious respiratory diseases. Many different devices, including thermometers, pulse oxim...

COV-MobNets: a mobile networks ensemble model for diagnosis of COVID-19 based on chest X-ray images.

BMC medical imaging
BACKGROUND: The medical profession is facing an excessive workload, which has led to the development of various Computer-Aided Diagnosis (CAD) systems as well as Mobile-Aid Diagnosis (MAD) systems. These technologies enhance the speed and accuracy of...

PeakDetective: A Semisupervised Deep Learning-Based Approach for Peak Curation in Untargeted Metabolomics.

Analytical chemistry
Peak-detection algorithms currently used to process untargeted metabolomics data were designed to maximize sensitivity at the sacrifice of selectively. Peak lists returned by conventional software tools therefore contain a high density of artifacts t...

Predicting the antigenic evolution of SARS-COV-2 with deep learning.

Nature communications
The relentless evolution of SARS-CoV-2 poses a significant threat to public health, as it adapts to immune pressure from vaccines and natural infections. Gaining insights into potential antigenic changes is critical but challenging due to the vast se...