Design Choices for Multimodal Transformer Learning with Missing and Longitudinal Healthcare Data

Multimodal learning offers the potential to improve predictions by integrating complementary information from heterogeneous data sources. However, multimodal datasets are frequently incomplete, raising important questions about how models should handle missing information. Although recent approaches