Machine learning algorithm being used to track Ebola infested bats

A team of scientists from the Cary Institute of Ecosystem Studies is using a machine learning algorithm to predict which bat species are most likely to carry Ebola. An article from Digital Trends notes that, over the past year or so, there have been a number of tech projects aimed at stopping the spread of Ebola, but this one in particular involves plotting the possible spread of Ebola and other filoviruses of the same family by predicting which species of bat are most likely to carry these diseases. [Native Advertisement] “This work entailed collecting intrinsic features describing the world’s bat species — 1,116 species altogether — and training a machine learning algorithm on these data to learn which features best predict the bat species that carry filoviruses,” lead author of…


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