Cancer prevalence estimates are used to guide policymaking, from prevention to screening programs. However, these data are only available for 28% of the U.S. population. We used deep learning to analyze satellite imagery in order to predict cancer prevalence with a high spatial resolution. This method explained up to 64.37% of the variation of cancer prevalence. It could potentially be used to map cancer prevalence in entire regions for which these estimates are currently unavailable.
展开▼
