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This AI Model Predicts People Will Get Sick The Most From Coronavirus
May 23, 2020
The coronavirus affects different people in different ways, with some experiencing mild symptoms, and others severe.  In this study from the University of New York, algorithms predicted with an accuracy of 70-80% the people who became extremely sick.
COVID-19 doesn’t create cookie cutter infections. Some people have extremely mild cases while others find themselves fighting for their lives .
Clinicians are working with limited resources against a disease that is very hard to predict. Knowing which patients are most likely to develop severe cases could help guide clinicians during this pandemic.
We are two researchers at New York University that study predictive analytics and infectious diseases . In early January, we realized that it was very possible the new coronavirus in China was going to make its way to New York and we wanted to develop a tool to help clinicians deal with the incoming surge of cases. We thought predictive analytics – a form of artificial intelligence – would be a good technology for this job.
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In a general sense, this type of AI looks at existing data to find patterns and then uses those patterns to make predictions about the future . Using data from 53 COVID-19 cases in January and February, we developed a group of algorithms to determine which mildly ill patients were likely become severely ill.
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