Author

Julien Broséus

Centre Hospitalier Régional et Universitaire de NancyORCID 0000-0002-6689-4006Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

David MeyreiD· 1 shared Ghislain FiévetiD· 1 shared Sébastien HergalantiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBioinformatics

David MeyreORCID

Mutual co-authors in cluster

Author profile →

1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintDec 9, 2025

The eXplainable Artificial Intelligence (XAI) Triad: Models, Importances, and Significance at Scale

Ghislain Fiévet, Julien Broséus, David Meyre, Sébastien Hergalant

This paper evaluates XAI methods for variable selection in biological data, finding that RF/Accuracy/PIMP performs best but is computationally intensive, while DT/Gini/simThresh offers a more scalable alternative.

DOI 10.64898/2025.12.06.692723

machine learning (classical)benchmarking

𝕏 PostBluesky