Abstract: This disclosure comprises a system, non-transitory computer readable storage medium and method for delivering medications and/or medical treatments that are appropriate to the resilient context of an individual patient. The resilient context comprises a predictive model for each of one or more patient function measures and a predictive model of patient resilience where said models are all developed by learning from the data associated with the individual patient. The medical advice, medical diagnoses and/or medical treatments may be provided “as is” and/or they may be customized to match the specific resilient context of the individual patient.

Abstract: This disclosure comprises a system, computer program product and apparatus for delivering medications and/or medical treatments that are appropriate to the resilient context of an individual patient. The resilient context comprises a predictive model for each of one or more patient function measures and a predictive model of patient resilience where said models are all developed by learning from the data associated with the individual patient. The medical advice, medical diagnoses and/or medical treatments may be provided “as is” and/or they may be customized to match the specific resilient context of the individual patient.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer readable storage medium, for using transfer learning to train a predictive model. In one aspect, a system receives predictive model training data. The training data and one or more training methods are used to train multiple predictive models. Variables and a predictive model type are then selected from the trained predictive models. The selected variables are then transferred into the selected type of predictive model as long as they reduce an error measure.