AI Medical Compendium Topic:
Pandemics

Clear Filters Showing 501 to 510 of 752 articles

Predicting Coronavirus Disease 2019 Infection Risk and Related Risk Drivers in Nursing Homes: A Machine Learning Approach.

Journal of the American Medical Directors Association
OBJECTIVE: Inform coronavirus disease 2019 (COVID-19) infection prevention measures by identifying and assessing risk and possible vectors of infection in nursing homes (NHs) using a machine-learning approach.

Pandemic number five - Latest insights into the COVID-19 crisis.

Biomedical journal
About nine months after the emergence of SARS-CoV-2, this special issue of the Biomedical Journal takes stock of its evolution into a pandemic. We acquire an elaborate overview of the history and virology of SARS-CoV-2, the epidemiology of COVID-19, ...

Dynamics and Development of the COVID-19 Epidemic in the United States: A Compartmental Model Enhanced With Deep Learning Techniques.

Journal of medical Internet research
BACKGROUND: Compartmental models dominate epidemic modeling. Transmission parameters between compartments are typically estimated through stochastic parameterization processes that depends on detailed statistics of transmission characteristics, which...

Toward automated severe pharyngitis detection with smartphone camera using deep learning networks.

Computers in biology and medicine
PURPOSE: Severe pharyngitis is frequently associated with inflammations caused by streptococcal pharyngitis, which can cause immune-mediated and post-infectious complications. The recent global pandemic of coronavirus disease (COVID-19) encourages th...

Efficient and Effective Training of COVID-19 Classification Networks With Self-Supervised Dual-Track Learning to Rank.

IEEE journal of biomedical and health informatics
Coronavirus Disease 2019 (COVID-19) has rapidly spread worldwide since first reported. Timely diagnosis of COVID-19 is crucial both for disease control and patient care. Non-contrast thoracic computed tomography (CT) has been identified as an effecti...

Predicting Psychological Distress Amid the COVID-19 Pandemic by Machine Learning: Discrimination and Coping Mechanisms of Korean Immigrants in the U.S.

International journal of environmental research and public health
The current study examined the predictive ability of discrimination-related variables, coping mechanisms, and sociodemographic factors on the psychological distress level of Korean immigrants in the U.S. amid the COVID-19 pandemic. Korean immigrants ...

Evaluation of the COVID-19 Pandemic Intervention Strategies with Hesitant F-AHP.

Journal of healthcare engineering
In this study, a hesitant fuzzy AHP method is presented to help decision makers (DMs), especially policymakers, governors, and physicians, evaluate the importance of intervention strategy alternatives applied by various countries for the COVID-19 pan...