Active learning for wearable health sensor

A method for tracking health data, comprising:

• a. receiving physical statistics data of a user;
• b. determining, with a machine learning model, a symptom prediction for said user based at least in part on said physical statistics data of said user, wherein said machine learning model has been trained by performing operations comprising:
• i. training said machine learning model to predict, for a health condition, health condition symptoms, and
• ii. re-training said machine learning model based at least in part on a training symptom report comprising feedback to a health condition symptom prediction of said machine learning model;
• and
• c. issuing a request for a symptom report to said user.

A method for tracking migraine headaches comprising:

• a. receiving physical statistics data of a user;
• b. determining, with a machine learning model, a migraine symptom prediction for said user based at least in part on said physical statistics data of said user;
• and
• c. issuing a request for a migraine symptom report for said user, wherein said request for said migraine symptom report comprises a request for feedback to said migraine symptom prediction such that a training dataset comprising at least said migraine symptom prediction and a response to said request for feedback comprises up-to-date and user-verified migraine symptom prediction information.