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"We had to use machine learning just to detect these seven patterns of disease in the first place," says Morris, whose team modified the technique known as multilayer non-negative matrix factorization. "And then we realized there are some children who do not fall into any of the patterns and they have a very bad version of the disease. Now we understand the disease much better we can group children into these different categories to predict response to treatment, how fast do they go into remission and whether or not we can tell they are in remission and remove therapy." - www.sciencedaily.com