Integrating multimodal data through interpretable heterogeneous ensembles.

ABSTRACT:

Motivation

Integrating multimodal data represents an effective approach to predicting biomedical characteristics, such as protein functions and disease outcomes. However, existing data integration approaches do not sufficiently address the heterogeneous semantics of multimodal data. In particular, early and intermediate approaches that rely on a uniform integrated representation reinforce the consensus among the modalities, but may lose exclusive local information. The alternative late integration approach that can address this challenge has not been systematically studied for biomedical problems.

Results

We propose Ensemble Integration (EI) as a novel systematic implementation of the late integration approach. EI infers local predictive models from the individual data modal

SUBMITTER: Li YC 

PROVIDER: S-EPMC9347276 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature