Develop robust, non-invasive methods to accurately stratify prostate cancer patients into various risk categories and allow for low-risk patients to get on to active surveillance and high-risk patients to receive radical therapies.

Efficient computational annotation of histologic primitives in the NEPTUNE dataset will enable discovery of structures that reveal molecular mechanisms or are prognostic biomarkers in future studies by consortium investigators. Project will develop and test foundational Apps (tool-box) of the NEPTUNE Digital Pathology-based Analytic hiSto-omicS intErrogation plaTform (NDP- ASSET) for segmentation of normal and pathologic classes of structural primitives

Aims to establish the computerized histologic risk predictor (CHiRP)—an approach that relies solely on computer extracted morphologic measurements from standard H&E tissue slide images to predict early recurrence in early stage non-small-cell lung cancer—as a predictive Affordable Precision Medicine solution.