most citedActiTect: A Generalizable Machine Learning Pipeline for REM Sleep Behavior Disorder Screening through Standardized Actigraphy

3 citations · 3 across the 4 of their papers we have counts for

collaborators

8 papers

q-bio.QM2026

Characterization of DLBCL cell of origin-phenotypes based on tumor microenvironment features

Stefano Ugliano, Martim Dias Gomes, Noémie Moreau +7

Diffuse large B-cell lymphoma (DLBCL) is an aggressive form of non-Hodgkin lymphoma with a high recurrence rate. The molecular profiling of DLBCL tumors culminated in several immun…

cs.CV2026

Self-Supervised ImageNet Representations for In Vivo Confocal Microscopy: Tortuosity Grading without Segmentation Maps

Kim Ouan, Noémie Moreau, Katarzyna Bozek

The tortuosity of corneal nerve fibers are used as indication for different diseases. Current state-of-the-art methods for grading the tortuosity heavily rely on expensive segmenta…

cs.LG20263 cited

ActiTect: A Generalizable Machine Learning Pipeline for REM Sleep Behavior Disorder Screening through Standardized Actigraphy

David Bertram, Anja Ophey, Sinah Röttgen +18

Isolated rapid eye movement sleep behavior disorder (iRBD) is a major prodromal marker of -synucleinopathies, often preceding the clinical onset of Parkinson's disease, dementi…

cs.CV2026

Understanding Cell Fate Decisions with Temporal Attention

Florian Bürger, Martim Dias Gomes, Adrián E. Granada +2

Understanding non-genetic determinants of cell fate is critical for developing and improving cancer therapies, as genetically identical cells can exhibit divergent outcomes under t…

cs.CV2026

Context-aware Skin Cancer Epithelial Cell Classification with Scalable Graph Transformers

Lucas Sancéré, Noémie Moreau, Katarzyna Bozek

Whole-slide images (WSIs) from cancer patients contain rich information that can be used for medical diagnosis or to follow treatment progress. To automate their analysis, numerous…

cs.CV2026

AMAP-APP: Efficient Segmentation and Morphometry Quantification of Fluorescent Microscopy Images of Podocytes

Arash Fatehi, David Unnersjö-Jess, Linus Butt +3

Background: Automated podocyte foot process quantification is vital for kidney research, but the established "Automatic Morphological Analysis of Podocytes" (AMAP) method is hinder…