I. Introduction
Precision medicine aims to provide diagnosis and treatment accounting for individual differences. To develop machine learning models in support of precision medicine, personalized or patient-specific models are expected to have better performance than one-model-fits-all approaches. A significant challenge, however, is the limited number of labeled samples for each individual due to cost, availability, and other practical constraints.