AIMC Topic: SARS-CoV-2

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[Advances in pulmonary pathology in China over the past ten years: retrospect and prospect].

Zhonghua bing li xue za zhi = Chinese journal of pathology
Over the past decade, China has made remarkable achievements in the updating of molecular characteristics and diagnostic criteria of lung cancer, pathological characteristics of COVID-19, classification scheme of interstitial lung disease, applicatio...

Artificial Intelligence Assessment of Chest Radiographs for COVID-19.

Clinical lymphoma, myeloma & leukemia
BACKGROUND: The sensitivity of reverse-transcription polymerase chain reaction (RT-PCR) is limited for diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Chest computed tomography (CT) is reported to have high sensitivity; how...

Using Machine Learning to Predict Uptake to an Online Self-Guided Intervention for Stress During the COVID-19 Pandemic.

Stress and health : journal of the International Society for the Investigation of Stress
Online self-guided interventions appear efficacious for alleviating some mental health concerns. However, among persons who are offered online interventions, only a fraction access them (i.e., achieve uptake). Machine learning methods may be useful t...

APNet, an explainable sparse deep learning model to discover differentially active drivers of severe COVID-19.

Bioinformatics (Oxford, England)
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
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
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
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
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
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
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...