AIMC Topic: COVID-19

Clear Filters Showing 581 to 590 of 2468 articles

Interface design of SARS-CoV-2 symmetrical nsp7 dimer and machine learning-guided nsp7 sequence prediction reveals physicochemical properties and hotspots for nsp7 stability, adaptation, and therapeutic design.

Physical chemistry chemical physics : PCCP
The COVID-19 pandemic, driven by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), necessitates a profound understanding of the virus and its lifecycle. As an RNA virus with high mutation rates, SARS-CoV-2 exhibits genetic variability lea...

FACNN: fuzzy-based adaptive convolution neural network for classifying COVID-19 in noisy CXR images.

Medical & biological engineering & computing
COVID-19 detection using chest X-rays (CXR) has evolved as a significant method for early diagnosis of the pandemic disease. Clinical trials and methods utilize X-ray images with computer and intelligent algorithms to improve detection and classifica...

Predicting humoral responses to primary and booster SARS-CoV-2 mRNA vaccination in people living with HIV: a machine learning approach.

Journal of translational medicine
BACKGROUND: SARS-CoV-2 mRNA vaccines are highly immunogenic in people living with HIV (PLWH) on effective antiretroviral therapy (ART). However, whether viro-immunologic parameters or other factors affect immune responses to vaccination is debated. T...

A stakeholder analysis to prepare for real-world evaluation of integrating artificial intelligent algorithms into breast screening (PREP-AIR study): a qualitative study using the WHO guide.

BMC health services research
BACKGROUND: The national breast screening programme in the United Kingdom is under pressure due to workforce shortages and having been paused during the COVID-19 pandemic. Artificial intelligence has the potential to transform how healthcare is deliv...

Machine Learning-Based Approach to Predict Last-Minute Cancellation of Pediatric Day Surgeries.

Computers, informatics, nursing : CIN
The last-minute cancellation of surgeries profoundly affects patients and their families. This research aimed to forecast these cancellations using EMR data and meteorological conditions at the time of the appointment, using a machine learning approa...

Key determinants to supply chain resilience to face pandemic disruption: An interpretive triple helix framework.

PloS one
Today, supply chain (SC) networks are facing more disruptions compared to the past. While disruptions are rare, they can have catastrophic long-term economic or societal repercussions, and the recovery processes can be lengthy. These can tremendously...

Exploring post-COVID-19 health effects and features with advanced machine learning techniques.

Scientific reports
COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health issues, and the loss of life. Among those who have recovered, many experience negative health effec...

Comprehensive Review on the Virulence Factors and Therapeutic Strategies with the Aid of Artificial Intelligence against Mucormycosis.

ACS infectious diseases
Mucormycosis, a rare but deadly fungal infection, was an epidemic during the COVID-19 pandemic. The rise in cases (COVID-19-associated mucormycosis, CAM) is attributed to excessive steroid and antibiotic use, poor hospital hygiene, and crowded settin...

Protocol to identify biomarkers in patients with post-COVID condition using multi-omics and machine learning analysis of human plasma.

STAR protocols
Here, we present a workflow for analyzing multi-omics data of plasma samples in patients with post-COVID condition (PCC). Applicable to various diseases, we outline steps for data preprocessing and integrating diverse assay datasets. Then, we detail ...