4 citations · 5 across the 4 of their papers we have counts for
6 papers · 1 filter
Hierarchical Bayesian Regression for Multi-Site Normative Modeling of Neuroimaging Data
Seyed Mostafa Kia, Hester Huijsdens, Richard Dinga +6
Clinical neuroimaging has recently witnessed explosive growth in data availability which brings studying heterogeneity in clinical cohorts to the spotlight. Normative modeling is a…
Neural Processes Mixed-Effect Models for Deep Normative Modeling of Clinical Neuroimaging Data
Seyed Mostafa Kia, Andre F. Marquand
Normative modeling has recently been introduced as a promising approach for modeling variation of neuroimaging measures across individuals in order to derive biomarkers of psychiat…
Scalable Multi-Task Gaussian Process Tensor Regression for Normative Modeling of Structured Variation in Neuroimaging Data
Seyed Mostafa Kia, Christian F. Beckmann, Andre F. Marquand
Most brain disorders are very heterogeneous in terms of their underlying biology and developing analysis methods to model such heterogeneity is a major challenge. A promising appro…
Normative Modeling of Neuroimaging Data using Scalable Multi-Task Gaussian Processes
Seyed Mostafa Kia, Andre Marquand
Normative modeling has recently been proposed as an alternative for the case-control approach in modeling heterogeneity within clinical cohorts. Normative modeling is based on sing…
Interpretability in Linear Brain Decoding
Seyed Mostafa Kia, Andrea Passerini
Improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no for…
Interpretability of Multivariate Brain Maps in Brain Decoding: Definition and Quantification
Seyed Mostafa Kia
Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. It is well known that the brain maps derived from weights of linear classifiers are hard t…