Fig. 4: Approaches for the combined use of multi-domain data resources to deliver personalized care.

Patient-reported and electronic health record abstracted data are routinely delivered as structured data resources for model training and inference. Image and signal data can be modeled directly (as unstructured data resources) or passed through validated AI-enabled analytics pipelines for feature extraction, then entered as structured data resources for prediction modeling. Composite data resources from each discrete data source can then be considered by ensemble-based prediction models to maximize prediction accuracy from available input models.