Predication of a headache

A system for predicting a headache for a subject by a machine learning model that is executing on the system, comprising:

• a processing circuitry;
• and
• a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:
• receive, by the machine learning model, a plurality of physiological, behavioral, and environmental parameters obtained from a plurality of sensors monitoring the subject;
• obtain, by the machine learning model, an indication of administered treatment in combination with the plurality of physiological, behavioral and environmental parameters;
• extract features from the plurality of sensors monitoring the subject;
• time-synchronize the features extracted from the plurality of sensors monitoring the subject;
• receive, by the machine learning model, the time-synchronized features in combination with the plurality of physiological, behavioral and environmental parameters;
• wherein the time-synchronizing may be performed by selecting different parameters that fall within a common time interval and feeding the parameters as vectors in the machine-learning model;
• and
• develop based on the machine learning model, the prediction of the headache for the subject;
• wherein the machine learning model is a trained machine learning model, wherein the system is further configured to train the machine learning model by:
• training the machine learning model on a first training dataset comprised of a first plurality of records wherein each record of the first plurality is developed for a respective one of sample individuals, wherein each record of the first plurality includes a plurality physiological, behavioral, and environmental parameters that are collected for the respective one of the sample individuals to which it pertains and a ground truth label indicative of a state of a headache of the respective one of the sample individuals, to which it pertains;
• and
• further training the machine learning model on a second training dataset comprised of a second plurality of records that are personalized records of the subject, wherein each personalized record of the second plurality of records includes a plurality of historical physiological, behavioral, and environmental parameters of the subject and a ground truth label indicative of the state of headache of the subject corresponding to a time of collection of the historical physiological, behavioral, and environmental parameters of the subject for each respective personalized record of the second plurality;
• wherein the prediction of the headache further includes a prediction of an adaptation of the treatment for preventing onset of the headache when the subject is not currently experiencing a headache or for reduction of severity of the headache currently experienced by the subject.