Current Topics in Machine Learning for Neuroimaging

The discovery of biological markers in medical applications is a fast-growing field. For this purpose, different experimental and neuroscientific procedures are incorporated to detect biological signatures and improve diagnosis or treatment of complex brain disorders. Neuroimaging is a discipline that studies the structure and function of the nervous system by means of imaging technology. In the recent years, machine and deep learning methods have revolutionized neuroimaging studies by enabling the development of imaging signatures of brain function and structure which can be detected at an individual level, and hence aid in developing personalized treatments. In this course, we explore the methodological gaps in analyzing high-dimensional, longitudinal, and heterogeneous clinical imaging and neuroscientific data and study novel, robust, scalable, and interpretable machine learning models for this purpose.