You are here: Machine Learning for Precision Health»Research overview

Research overview

Our research makes diagnoses and prognoses more quantitative and individualized for clinical neuroscience applications including neuropsychiatric, neurodegenerative, neurodevelopmental brain disorders, and oncological applications.

These new capabilities enhance triage criteria, improve patient management, and refine inclusion criteria for clinical trials to enable faster development of new treatments. For a given application, we identify the best existing data acquisition and analysis methods, and then improve the acquisition, reconstruction, and imaging–genomic feature extraction methods in a systematic manner beginning where limitations are greatest.

Next, we build an optimal discriminative learning method to engender individualized predictions that have state-of-the art accuracy. To make the research most advantageous, we engender an interdependent research environment with the best collaborators and link our efforts to funding opportunities.