We have multimodal machine learning projects underway. Some of these involve stratifying outputs of vision models with associated demographic variables (age, sex, race/ethnicity etc.) to determine efficacy. Others we have ongoing represent fusion models in which we are learning from structured fields in context with vision-derived inputs/embeddings and clinical note embeddings.