Walid M. Abdelmoula

massNet uses deep learning to classify spatial mass spectrometry data without preprocessing, achieving higher accuracy and faster speed than classical methods for tumor delineation in mouse brain tissue.

MIAAIM integrates multimodal imaging data across tissue types to map tissue states and link cellular phenotypes with molecular microenvironments.

The paper introduces msiPL, a deep learning model for analyzing MSI data, enabling efficient non-linear visualization and identification of biologically relevant patterns.