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World is now experiencing a major health calamity due to the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus clade 2. The foremost challenge facing the scientific community is to explore the growth and transmission capability of the virus. Use of artificial intelligence (AI), such as deep learning, in (i) rapid disease detection from x-ray or computed tomography (CT) or high-resolution CT (HRCT) images, (ii) accurate prediction of the epidemic patterns and their saturation throughout the globe, (iii) forecasting the disease and psychological impact on the population from social networking data, and (iv) prediction of drug-protein interactions for repurposing the drugs, has attracted much attention. In the present study, we describe the role of various AI-based technologies for rapid and efficient detection from CT images complementing quantitative real-time polymerase chain reaction and immunodiagnostic assays. AI-based technologies to anticipate the current pandemic pattern, prevent the spread of disease, and face mask detection are also discussed. We inspect how the virus transmits depending on different factors. We investigate the deep learning technique to assess the affinity of the most probable drugs to treat COVID-19. This article is categorized under:Application Areas > Health CareAlgorithmic Development > Biological Data MiningTechnologies > Machine Learning.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9350133 | PMC |
http://dx.doi.org/10.1002/widm.1462 | DOI Listing |
Int J Med Microbiol
September 2025
Center for Infectious Diseases and Pathogen Biology, The First Hospital of Jilin University, Jilin University, Changchun, Jilin 130000, China; Research Institute of Virology and AIDS research, The First Hospital of Jilin University, Jilin University, Changchun, Jilin 130000, China. Electronic addres
The emergence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) as the causative agent of COVID-19 precipitated a global health crisis of unprecedented scale. SARS-CoV-2 has been shown to interfere specifically with S phase progression during early stages of infection. Nucleocapsid (N) is an important structural protein.
View Article and Find Full Text PDFJ Bras Nefrol
September 2025
Centro de Asistencia del Sindicato Médico del Uruguay (CASMU), Institución de Asistencia Médica Privada de Profesionales sin fines de lucro (IAMPP), Departamento de Nefrología, Montevideo, Uruguay.
Introduction: Acute kidney disease (AKD) is defined as functional and/or structural abnormalities of kidneys with health implications and a duration of ≤90 days. This study aimed to evaluate AKD as a more appropriate approach to these conditions for which we used a cohort of COVID-19 patients in whom kidney impairment is expressed by proteinuria and/or loss of function.
Methods: Observational, prospective, longitudinal, multinational cohort study conducted across five Latin American countries.
Pediatr Pulmonol
September 2025
Department of Pediatrics, Division of Pediatric Allergy, Immunology and Pulmonary Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Background: Children with tracheostomies require skilled medical care performed by trained caregivers or home health nursing (HHN). HHN services are often limited, resulting in increased caregiver responsibilities. We aim to evaluate HHN availability, healthcare utilization, and mortality in tracheostomy dependent children, pre and post-COVID-19 pandemic.
View Article and Find Full Text PDFEur J Pediatr
September 2025
Neonatal and Pediatric Intensive Care Unit, Intermediate Care Unit, Emergency Department, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147, Genoa, Italy.
Unlabelled: Benign Acute Childhood Myositis (BACM) is a transient, self-limiting muscular condition that typically follows viral infections, especially influenza. The COVID-19 pandemic disrupted the circulation of respiratory viruses, altering the epidemiology of related post-infectious complications. This study investigates trends in BACM incidence, clinical features, and viral etiology before and after the pandemic.
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