Context-aware prediction in medical systems

A system for context-aware prediction of medical conditions, comprising:

• a first computing device comprising a memory including processor-executable instructions and a processor configured to execute instructions from the memory;
• wherein the instructions include instructions for the processor to:
• receive contextual data and outcome data;
• create a feature set from the contextual data;
• select a plurality of feature subsets from the feature set;
• apply each of the plurality of feature subsets and the outcome data to a classifier, and determine a score for each of the plurality of feature subsets;
• select a preferred feature subset based on the score for each of the plurality of feature subsets;
• and
• generate a prediction model of an outcome using the preferred feature subset;
• and
• an interface providing access to the prediction model by a second computing device;
• wherein the prediction model is configured to input subject data received from a monitoring device, make a prediction based on the received subject data regarding a likelihood of the outcome occurring, and output the prediction to the second computing device,
• wherein the outcome data represents at least one outcome, and wherein the instructions to determine the score for each of the plurality of feature subsets includes instructions for the processor to, for each feature subset:
• use the classifier to determine a probability measure for each feature in the feature subset, the probability measure being an indication of how predictive the feature is for an outcome of the at least one outcome;
• create a characteristic curve of true positive rate versus false positive rate, wherein each point of the characteristic curve represents a portion of the feature set, and each portion of the feature set is selected based on a probability measure threshold;
• and
• calculate the score as an area under the characteristic curve.