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According to Eurek Alert!, the assessment has an accuracy rate of around 90 percent after analyzing the data of almost 4,000 Danes who suffered from COVID-19. Health experts hope to use the tool in order to understand which members of the population should receive the vaccine first and make a more effective roll-out in the midst of second waves occurring across the globe. In addition, the model was also able to predict with around 80 percent accuracy which patients would need a respirator if infected. This information could help doctors better care for patients by knowing almost immediately who will be requiring the machines and hopefully save lives in the process. Health experts hope that combining infection rate patterns with the population s health data will be able to predict which hospitals should be sent respirators to avoid shortages in the event of a sudden outbreak.

Astrazeneca covidHeathcliff omalley gettyUniversity of copenhagen department computer scienceUniversity of copenhagenLab techniciansProfessor mads nielsenHeathcliffo malleyCorona virusஹீத் கிளிஃப் ஓமல்லேய் கெட்டிபல்கலைக்கழகம் ஆஃப் கோபெந்ஹேகந் துறை கணினி அறிவியல்பல்கலைக்கழகம் ஆஃப் கோபெந்ஹேகந்ஆய்வகம் தொழில்நுட்ப வல்லுநர்கள்ப்ரொஃபெஸர் மாட்ஸ் நீல்சன்கொரோனா வைரஸ்