Health-related metric explainer

An apparatus, comprising:

• at least one processor;
• at least one memory coupled with the at least one processor;
• and
• instructions stored in the at least one memory and executable by the at least one processor to cause the apparatus to:
• predict, using a first machine learning model, a future physiological metric from a set of feature vectors of a first set of physiological data measured from a user via a wearable device;
• generate, using a second machine learning model, a set of correlation values indicating a predictive weighting for each feature vector of the set of feature vectors for predicting the future physiological metric;
• generate a plurality of clustered groups of feature vectors, wherein the plurality of clustered groups of feature vectors are clustered according to preconfigured associations with user-recognizable categories;
• and
• cause a graphical user interface (GUI) of the apparatus associated with the wearable device to output an indication of one or more clustered groups of the plurality of clustered groups that comprise a cumulative weighting that exceeds a predetermined threshold based at least in part on the set of correlation values associated with the respective feature vectors.

A non-transitory computer-readable medium storing code, the code comprising instructions executable by a processor to:

• predict, using a first machine learning model, a future physiological metric from a set of feature vectors of a first set of physiological data measured from a user via a wearable device;
• generate, using a second machine learning model, a set of correlation values indicating a predictive weighting for each feature vector of the set of feature vectors for predicting the future physiological metric;
• generate a plurality of clustered groups of feature vectors, wherein the plurality of clustered groups of feature vectors are clustered according to preconfigured associations with user-recognizable categories;
• and
• cause a graphical user interface (GUI) of a user device associated with the wearable device to output an indication of one or more clustered groups of the plurality of clustered groups that comprise a cumulative weighting that exceeds a predetermined threshold based at least in part on the set of correlation values associated with the respective feature vectors.