Multi-modal Modeling in Precision Medicine: From Data Imputation to Synthetic Data

• how cross-modal data modeling uses one data type (like imaging) to fill in gaps in another data type (like genomics).
• ongoing multi-modal modeling efforts in spatial omics, digital pathology, and radiology.
• how multi-modal modeling is anticipated to help us better understand disease biology and improve healthcare practices.

Multi-modal modeling can empower researchers, like you, to model complex interactions among diverse biomedical data types (including omics and imaging). Attend this seminar and get a better understanding of how one modality influences another, facilitating in-silico exploration of disease mechanisms without the need for extensive and costly real-world data collection