AIMC Topic: COVID-19

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Usefulness of machine learning in COVID-19 for the detection and prognosis of cardiovascular complications.

Reviews in cardiovascular medicine
Since January 2020, coronavirus disease 2019 (COVID-19) has rapidly become a global concern, and its cardiovascular manifestations have highlighted the need for fast, sensitive and specific tools for early identification and risk stratification. Mach...

Survival Analysis of COVID-19 Patients in Russia Using Machine Learning.

Studies in health technology and informatics
The current pandemic can likely have several waves and will require a major effort to save lives and provide optimal treatment. The efficient clinical resource planning and efficient treatment require identification of risk groups and specific clinic...

COVID-19 and the epistemology of epidemiological models at the dawn of AI.

Annals of human biology
The models used to estimate disease transmission, susceptibility and severity determine what epidemiology can (and cannot tell) us about COVID-19. These include: 'model organisms' chosen for their phylogenetic/aetiological similarities; multivariable...

Artificial intelligence technology for diagnosing COVID-19 cases: a review of substantial issues.

European review for medical and pharmacological sciences
Today, the world suffers from the rapid spread of COVID-19, which has claimed thousands of lives. Unfortunately, its treatment is yet to be developed. Nevertheless, this phenomenon can be decelerated by diagnosing and quarantining patients with COVID...

Editorial perspective September 2020 JVN issue.

Journal of vascular nursing : official publication of the Society for Peripheral Vascular Nursing

Artificial intelligence in ophthalmology during COVID-19 and in the post COVID-19 era.

Current opinion in ophthalmology
PURPOSE OF REVIEW: To highlight artificial intelligence applications in ophthalmology during the COVID-19 pandemic that can be used to: describe ocular findings and changes correlated with COVID-19; extract information from scholarly articles on SARS...