Integrating medical imaging and cancer biology with deep neural networks

Despite our remarkable advances in medicine and healthcare, the cure to cancer continues to elude us. On the bright side, we have made considerable progress in detecting several cancers in earlier stages, allowing doctors to provide treatments that increase long-term survival. The credit for this is due to "integrated diagnosis," an approach to patient care that combines molecular information and medical imaging data to diagnose the cancer type and, eventually, predict treatment outcomes. There are, however, several intricacies involved. The correlation of molecular patterns, such as gene expression and mutation, with image features (e.g., how a tumor appears in a CT scan), is commonly referred to as "radiogenomics."