In the Imaging Informatics for Interventions (INVent) Laboratory, we develop artificial intelligence (AI) schemes to assist the clinician toward enabling precision medicine by “unlocking” embedded information captured by different data modalities, in an intuitive and generalizable fashion. Specifically, we focus on new image analytics, radiomics, and machine learning methods that can capture biologically relevant and clinically intuitive measurements from routinely acquired imaging. Uniquely, we attempt to integrate information across multiple length scales of Big Data by spatially resolving and cross-linking imaging (macro-scale) with molecular and pathology (micro-, nano- scales) data. We have also developed tools and approaches toward enabling these AI models to be repeatable across imaging parameters as well as reproducible across institution- or scanner-specific variations. As a result, we can obtain a more comprehensive, interpretable, generalizable, and quantitative assessment of disease in vivo. Learn more about our research efforts.