Abstract: Disclosed is a method comprising accessing, by a machine learning system, a set of data records for a plurality of users, the data records representative of physical statistics measured for each of the plurality of users over a time period. At least a subset of the data records comprises patterns of missing data for at least a portion of the time period. The method also comprises generating a set of masked data records by masking a subset of the data records in accordance with a pattern of natural missingness from a data record. The method also comprises generating, by the machine learning system, a set of learned representations from at least the set of masked data records. Finally, the method comprises fine tuning, by the machine learning system, a machine learning model using the set of learned representations, the machine learning model configured to perform a downstream machine learning task.