AIMC Topic: COVID-19
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Machine Learning-Based Approach to Predict Last-Minute Cancellation of Pediatric Day Surgeries.
Computers, informatics, nursing : CIN
May 1, 2024
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
May 1, 2024
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...
On Minimizers and Convolutional Filters: Theoretical Connections and Applications to Genome Analysis.
Journal of computational biology : a journal of computational molecular cell biology
Apr 30, 2024
Exploring post-COVID-19 health effects and features with advanced machine learning techniques.
Scientific reports
Apr 30, 2024
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
Apr 29, 2024
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
Apr 27, 2024
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 ...
Co-Mutations and Possible Variation Tendency of the Spike RBD and Membrane Protein in SARS-CoV-2 by Machine Learning.
International journal of molecular sciences
Apr 25, 2024
Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, SARS-CoV-2 variants capable of breakthrough infections have attracted global attention. These variants have significant mutations in the receptor-binding domain (RBD) of the spike p...
Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning.
PloS one
Apr 25, 2024
The Omicron SARS-CoV-2 variant continues to strain healthcare systems. Developing tools that facilitate the identification of patients at highest risk of adverse outcomes is a priority. The study objectives are to develop population-scale predictive ...
Identification of Age-Related Characteristic Genes Involved in Severe COVID-19 Infection Among Elderly Patients Using Machine Learning and Immune Cell Infiltration Analysis.
Biochemical genetics
Apr 24, 2024
Elderly patients infected with severe acute respiratory syndrome coronavirus 2 are at higher risk of severe clinical manifestation, extended hospitalization, and increased mortality. Those patients are more likely to experience persistent symptoms an...
Construction and validation of machine learning algorithm for predicting depression among home-quarantined individuals during the large-scale COVID-19 outbreak: based on Adaboost model.
BMC psychology
Apr 24, 2024
OBJECTIVES: COVID-19 epidemics often lead to elevated levels of depression. To accurately identify and predict depression levels in home-quarantined individuals during a COVID-19 epidemic, this study constructed a depression prediction model based on...
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