A MULTI-MODAL APPROACH TO PREDICTING IMMUNE INFILTRATION BASED ON INTEGRATED RNA EXPRESSION AND IMAGING FEATURES

摘要

Multi-modal approaches to predict tumor immune infiltration are based on integrating gene expression data and imaging features in a neural network-based framework. This framework is configured to estimate percent composition, and thus immune infiltration score, of a patient tumor biopsy sample. Multi-modal approaches may also be used to predict cell composition beyond immune cells via integrated multi-layer neural network frameworks.