3 papers
cs.LG2025
Masked Omics Modeling for Multimodal Representation Learning across Histopathology and Molecular Profiles
Lucas Robinet, Ahmad Berjaoui, Elizabeth Cohen-Jonathan Moyal
Self-supervised learning (SSL) has driven major advances in computational pathology by enabling the learning of rich representations from histopathology data. Yet, tissue analysis…
cs.CV2025
Multimodal Masked Autoencoder Pre-training for 3D MRI-Based Brain Tumor Analysis with Missing Modalities
Lucas Robinet, Ahmad Berjaoui, Elizabeth Cohen-Jonathan Moyal
Multimodal magnetic resonance imaging (MRI) constitutes the first line of investigation for clinicians in the care of brain tumors, providing crucial insights for surgery planning,…
cs.AI2024
DRIM: Learning Disentangled Representations from Incomplete Multimodal Healthcare Data
Lucas Robinet, Ahmad Berjaoui, Ziad Kheil +1
Real-life medical data is often multimodal and incomplete, fueling the growing need for advanced deep learning models capable of integrating them efficiently. The use of diverse mo…