Book chapter: Integration of Multimodal Data
Published in Springer US, 2023
This chapter focuses on the joint modeling of heterogeneous information, such as imaging, clinical, and biological data. This kind of problem requires to generalize classical uni- and multivariate association models to account for complex data structure and interactions, as well as high data dimensionality.
Recommended citation: Lorenzi, M., Deprez, M., Balelli, I., Aguila, A. L., & Altmann, A. (2012). Integration of Multimodal Data. In Machine Learning for Brain Disorders (pp. 573-597). New York, NY: Springer US.