Nice job. Now you really need to study up on the statistics behind this and you'll quickly come to the conclusion that this was the easy part. What to do with the output is the hard part. I've seen a start-up that made their bread and butter on such classifications, they did an absolutely great job of it but found the the problem of deciding what to do with such an application without ending up with net negative patient outcomes to be far, far harder than the classification problem itself. The error rates, no matter how low, are going to be your main challenge, both false positives and false negatives can be extremely expensive, both in terms of finance and in terms of emotion.
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