High-order Connectomic Manifold Learning for Autistic Brain State Identification. - Mayssa Soussia; Islem Rekik (CNI@MICCAI, 2017)

Unsupervised Manifold Learning Using High-Order Morphological Brain Networks Derived From T1-w MRI for Autism Diagnosis. - Mayssa Soussia; Islem Rekik (Frontiers Neuroinformatics, 2018)

7 Years of Developing Seed Techniques for Alzheimer's Disease Diagnosis Using Brain Image and Connectivity Data Largely Bypassed Prediction for Prognosis. - Mayssa Soussia; Islem Rekik (PRIME@MICCAI, 2019)

A Computational Framework for Dissociating Development-Related from Individually Variable Flexibility in Regional Modularity Assignment in Early Infancy. - Mayssa Soussia; Xuyun Wen; Zhen Zhou 004; Bing Jin; Tae-Eui Kam; Li-Ming Hsu; Zhengwang Wu; Gang Li 001; Li Wang 026; Islem Rekik; Weili Lin; Dinggang Shen; et al. (MICCAI (7), 2020)

Generative Hypergraph Neural Network for Multiview Brain Connectivity Fusion. - Mayssa Soussia; Mohamed Ali Mahjoub; Islem Rekik (PRIME@MICCAI, 2024)

Multi-Sensory Cognitive Computing for Learning Population-level Brain Connectivity. - Mayssa Soussia; Mohamed Ali Mahjoub; Islem Rekik (CoRR, 2025)