The scientists then used machine learning to analyze the data. First, they trained their computer program—a deep learning algorithm loosely modeled on how neurons work in the brain—on 95 different species of bacteria from 90% of the samples, along with the ages of the people they had come from. Then, they asked the algorithm to predict the ages of the people who provided the remaining 10%. Their program was able to accurately predict someone’s age within 4 years, they report on the preprint server bioRxiv. Out of the 95 species of bacteria, 39 were found to be most important in predicting age.
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