AIMC Topic:
SARS-CoV-2
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APNet, an explainable sparse deep learning model to discover differentially active drivers of severe COVID-19.
Bioinformatics (Oxford, England)
Mar 4, 2025
MOTIVATION: Computational analyses of bulk and single-cell omics provide translational insights into complex diseases, such as COVID-19, by revealing molecules, cellular phenotypes, and signalling patterns that contribute to unfavourable clinical out...
COVID-19 Patients Benefitting From Remdesivir for Improved Survival: A Neural Network-Based Approach.
Journal of medical virology
Mar 1, 2025
Conflicting results from randomized trials regarding the efficacy of remdesivir for COVID-19 have been reported. We aimed to develop a neural network (NN) to identify COVID-19 patients who would derive the greatest survival benefit from remdesivir. T...
A Double Machine Learning Approach for the Evaluation of COVID-19 Vaccine Effectiveness Under the Test-Negative Design: Analysis of Québec Administrative Data.
Statistics in medicine
Feb 28, 2025
The test-negative design (TND), which is routinely used for monitoring seasonal flu vaccine effectiveness (VE), has recently become integral to COVID-19 vaccine surveillance, notably in Québec, Canada. Some studies have addressed the identifiability ...
AI-driven health analysis for emerging respiratory diseases: A case study of Yemen patients using COVID-19 data.
Mathematical biosciences and engineering : MBE
Feb 24, 2025
In low-income and resource-limited countries, distinguishing COVID-19 from other respiratory diseases is challenging due to similar symptoms and the prevalence of comorbidities. In Yemen, acute comorbidities further complicate the differentiation bet...
Machine learning algorithm approach to complete blood count can be used as early predictor of COVID-19 outcome.
Journal of leukocyte biology
Feb 13, 2025
Although the SARS-CoV-2 infection has established risk groups, identifying biomarkers for disease outcomes is still crucial to stratify patient risk and enhance clinical management. Optimal efficacy of COVID-19 antiviral medications relies on early a...
Using minor variant genomes and machine learning to study the genome biology of SARS-CoV-2 over time.
Nucleic acids research
Feb 8, 2025
In infected individuals, viruses are present as a population consisting of dominant and minor variant genomes. Most databases contain information on the dominant genome sequence. Since the emergence of SARS-CoV-2 in late 2019, variants have been sele...
The Impact of AI-driven Remote Patient Monitoring on Cancer Care: A Systematic Review.
Anticancer research
Feb 1, 2025
The coronavirus disease 2019 (COVID-19) pandemic necessitated a shift in healthcare delivery, emphasizing the need for remote patient monitoring (RPM) to minimize infection risks. This review aimed to evaluate the applications of artificial intellige...
A causal machine-learning framework for studying policy impact on air pollution: a case study in COVID-19 lockdowns.
American journal of epidemiology
Jan 8, 2025
When studying the impact of policy interventions or natural experiments on air pollution, such as new environmental policies or the opening or closing of an industrial facility, careful statistical analysis is needed to separate causal changes from o...
Surface-Enhanced Raman Scattering Nanotags: Design Strategies, Biomedical Applications, and Integration of Machine Learning.
Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology
Jan 1, 2025
Surface-enhanced Raman scattering (SERS) is a transformative technique for molecular identification, offering exceptional sensitivity, signal specificity, and resistance to photobleaching, making it invaluable for disease diagnosis, monitoring, and s...
Leveraging artificial intelligence to promote COVID-19 appropriate behaviour in a healthcare institution from north India: A feasibility study.
The Indian journal of medical research
Jan 1, 2025
Background & Objectives Non-pharmacological interventions (NPI) were crucial in curbing the initial COVID-19 pandemic waves, but compliance was difficult. The primary aim of this study was to assess the changes in compliance with NPIs in healthcare s...
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