MACHINE LEARNING-BASED INVARIANT DATA REPRESENTATION

A system and method for predicting a condition of a subject may include one or more autoencoder modules, trained to: receive at least one content data element pertaining to the subject from one or more data sources of a plurality of data sources; and generate a source-invariant representation of the at least one content data element in a latent space of the one or more autoencoders. One or more machine-learning (ML) based classification models may receive the source-invariant representation of the at least one content data element, and produce therefrom a prediction data element, which may represent a predicted condition of the subject.