Example 1: AIM-AI: an Actionable, Integrated and Multiscale genetic map of Alzheimer's disease via deep learning. This project is an extension of a funded NIH U01 (U01AG079847) (PI: Zhao, Gaiteri, & Jiang). The goal is to generate a robust AIM-AI framework, including machine learning methods and tools, resources, and scientific discoveries, which will be immediately shared with AD researchers and other complex disease research communities.
Example 2: Predicting Phenotype by Deep Learning Heterogeneous Multi-Omics Data. This project is an extension of a funded NIH R01 (R01LM012806) (PI: Zhao). The goal is to combine multi-omics, phenotype, AI models, and electronic medical record (EMR) data mining to develop novel analytical strategies that maximally leverage regulatory information in phenotype prediction.
Example 3: Personalized, antigen-directed immunotherapy delivered to lymph nodes. This project is an extension of a funded NIH R01 (R01CA276513) (PI: Sevick, Mohsen, & Zhao). The goal is to use state-of the-art technologies of imaging, world-renowned expertise in cancer vaccine design and production, single cell RNA sequencing, immunoprofiling, and multiplex immunofluorescence to show that by harnessing the lymphatics, immune responses can be personalized. The implications for this research extend beyond cancer to autoimmune and infectious diseases that benefit by immunomodulatory interventions.
