| CPC G16H 50/30 (2018.01) [G16H 50/20 (2018.01)] | 23 Claims |
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1. A computing system comprising:
a processor; and
a memory coupled to the processor, the memory including a set of instructions, which when executed by the processor, cause the computing system to:
identify minority class data and majority class data in patient-level data, wherein the minority class data corresponds to patients with a health failure and the majority class data corresponds to patients without the health failure;
oversample the minority class data to obtain synthetic class data; and
automatically reduce, via a machine learning classifier, risk factor variables to a reduced set of risk factor variables based on the majority class data, the minority class data and the synthetic class data, wherein the machine learning classifier includes a multi-layer neural network configured to be trained using at least a portion of the patient-level data to perform one or more forward propagations and one or more rearward propagations until a value of a loss function is acceptable.
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