Forecasting and explaining user health metrics

A system for predicting a health metric of a user, the system comprising:

• one or more processors;
• and
• a memory storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising:
• receiving a plurality of health measurements for the user;
• determining a set of features based on the health measurements, wherein the features are classified into a set of feature groups, each feature group being associated with a health factor;
• generating a prediction of the health metric by inputting the features into a machine learning model, wherein the prediction includes a probability that the health metric will reach a target value or range at a future time period;
• identifying at least one feature group that provided a threshold contribution to the prediction;
• and
• outputting a notification for the user including the prediction and an indication of the at least one feature group.

A non-transitory computer-readable storage medium including instructions that, when executed by a computing system, cause the computing system to perform operations comprising:

• receiving health data of a user, wherein the health data includes measurements for a plurality of health factors;
• determining a plurality of features from the health data, wherein the features are categorized into a plurality of feature groups, each feature group being associated with a corresponding health factor;
• generating a prediction of a health metric of the user at a future time point by inputting the features into a machine learning model;
• determining a contribution of each feature group to the prediction;
• and
• outputting a notification to the user including the prediction and a health factor associated with a feature group having the largest contribution to the prediction.