Machine Learning in Neuroimaging: Applications to Clinical Neuroscience and Neurooncology

Machine learning has deeply penetrated the neuroimaging field in the past 15 years, by providing a means to construct imaging signatures of normal and pathologic brain states on an individual person basis. In this talk, I will discuss examples from our laboratory’s work on imaging signatures of brain aging and early stages of neurodegenerative diseases, brain development and neuropsychiatric disorders, as well as brain cancer precision diagnostics and estimation of molecular characteristics. I will discuss some challenges, such as disease heterogeneity and integration and harmonization of large datasets in multi-institutional consortia. I will present some of our work in these directions.