AIMC Topic: COVID-19

Clear Filters Showing 2171 to 2180 of 2468 articles

Streamlining social media information retrieval for public health research with deep learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Social media-based public health research is crucial for epidemic surveillance, but most studies identify relevant corpora with keyword-matching. This study develops a system to streamline the process of curating colloquial medical diction...

Predicting the transmission trends of COVID-19: an interpretable machine learning approach based on daily, death, and imported cases.

Mathematical biosciences and engineering : MBE
COVID-19 is caused by the SARS-CoV-2 virus, which has produced variants and increasing concerns about a potential resurgence since the pandemic outbreak in 2019. Predicting infectious disease outbreaks is crucial for effective prevention and control....

Transforming Public Health Practice With Generative Artificial Intelligence.

Health affairs (Project Hope)
Public health practice appears poised to undergo a transformative shift as a result of the latest advancements in artificial intelligence (AI). These changes will usher in a new era of public health, charged with responding to deficiencies identified...

Teleneurology and Artificial Intelligence in Clinical Practice.

Continuum (Minneapolis, Minn.)
As teleheath becomes integrated into the practice of medicine, it is important to understand the benefits, limitations, and variety of applications. Telestroke was an early example of teleneurology that arose from a need for urgent access to neurolog...

Mutation prediction in the SARS-CoV-2 genome using attention-based neural machine translation.

Mathematical biosciences and engineering : MBE
Severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) has been evolving rapidly after causing havoc worldwide in 2020. Since then, it has been very hard to contain the virus owing to its frequently mutating nature. Changes in its genome lead t...

Machine learning to understand risks for severe COVID-19 outcomes: a retrospective cohort study of immune-mediated inflammatory diseases, immunomodulatory medications, and comorbidities in a large US health-care system.

The Lancet. Digital health
BACKGROUND: In the context of immune-mediated inflammatory diseases (IMIDs), COVID-19 outcomes are incompletely understood and vary considerably depending on the patient population studied. We aimed to analyse severe COVID-19 outcomes and to investig...

Analysis of Critical Incident Reports Using Natural Language Processing.

Studies in health technology and informatics
UNLABELLED: A Critical Incident Reporting System (CIRS) collects anecdotal reports from employees, which serve as a vital source of information about incidents that could potentially harm patients.

Development of a machine learning model and nomogram to predict seizures in children with COVID-19: a two-center study.

Journal of tropical pediatrics
OBJECTIVE: This study aimed to use machine learning to evaluate the risk factors of seizures and develop a model and nomogram to predict seizures in children with coronavirus disease 2019 (COVID-19).

Genotypic-phenotypic landscape computation based on first principle and deep learning.

Briefings in bioinformatics
The relationship between genotype and fitness is fundamental to evolution, but quantitatively mapping genotypes to fitness has remained challenging. We propose the Phenotypic-Embedding theorem (P-E theorem) that bridges genotype-phenotype through an ...