Artificial intelligence-based methods for fusion of electronic health records and imaging data.

ABSTRACT: Healthcare data are inherently multimodal, including electronic health records (EHR), medical images, and multi-omics data. Combining these multimodal data sources contributes to a better understanding of human health and provides optimal personalized healthcare. The most important question when using multimodal data is how to fuse them-a field of growing interest among researchers. Advances in artificial intelligence (AI) technologies, particularly machine learning (ML), enable the fusion of these different data modalities to provide multimodal insights. To this end, in this scoping review, we focus on synthesizing and analyzing the literature that uses AI techniques to fuse multimodal medical data for different clinical applications. More specifically, we focus on studies that only fused

SUBMITTER: Mohsen F 

PROVIDER: S-EPMC9605975 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature