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Machine Learning Helping in Coronavirus as a Tool of Information

Coronavirus map
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The widespread of Coronavirus is not going to be stopped with the help of AI or Machine Learning but these tools can help to mine the information of the disease. For the first time, Machine Learning is becoming a useful tool in data gathering for the global outbreak of disease.

Machine Learning works on the data, the more data the more it is going to perform great. In the initial phase of coronavirus the Algorithm was able to provide limited result but due to millions of users posting updates for the disease spread created a large amount of data that can help the Algorithm. “The field has evolved dramatically,” said John Brownstein, a computational epidemiologist at Boston Children’s Hospital, He operates a public health surveillance site called that uses AI and Machine Learning to analyze data from government reports, social media, news sites, and other sources. The algorithm is currently mining news and social media.


A Canadian Firm BlueDot used Machine Learning and predicted the widespread of Coronavirus on December 31. It used datapoints from animal and plant disease, news reports in vernacular websites, government documents and other online sources. BlueDot used airline ticketing data to predict that the virus would spread to Bangkok, Tokyo and other parts of the world. Machine Learning and NLP (Natural Language Processing) were used to create the learning models that process large amounts of data in real-time. After this system gives the result, the result gets diagnosed by the trained epidemiologists who draw inferences and attach a risk factor to each case.



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