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Irvine, Calif., Dec. 17, 2020 University of California, Irvine health sciences researchers have created a machine-learning model to predict the probability that a COVID-19 patient will need a ventilator or ICU care. The tool is free and available online for any healthcare organization to use. The goal is to give an earlier alert to clinicians to identify patients who may be vulnerable at the onset, said Daniel S. Chow, an assistant professor in residence in radiological sciences and first author of the study, published in
PLOS ONE. The tool predicts whether a patient s condition will worsen within 72 hours.
Coupled with decision-making specific to the healthcare setting in which the tool is used, the model uses a patient s medical history to determine who can be sent home and who will need critical care. The study found that at UCI Health, the tool s predictions were accurate about 95 percent of the time.
Not an air purifier, but a COVID-killer | Brandywine Hundred company is 1st in Northeast to install revolutionary tech
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Researchers create model to calculate COVID-19 health outcomes
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4 min de lectura
Unquestionably, Honduras portrays the tale of a country that is experiencing dire symptoms of a failed state symptoms that have been accelerated by a pandemic and two hurricanes, but have been nurtured by weak state capacity, corruption and poor rule of law.
Can the people save the people?
Concepts like legitimacy and trust in government have transcended theory - they are vital for effective distribution of humanitarian aid.
As relief efforts continue, NGO’s, both domestic and international, are reluctant towards working alongside the government. During the hurricanes, groups of citizens rushed to flooded neighborhoods with boats to save people that were left stranded on their rooftops, others prepared supplies, volunteered and donated to shelters.