Author

Philipp Baumann

Centre Hospitalier Universitaire VaudoisORCID 0000-0002-3286-4474Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:imaging· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Patric HagmanniD· 2 shared Philippe ConusiD· 2 shared Ane López‐GonzáleziD· 1 shared Benjamin ChiêmiD· 1 shared Gustavo DecoiD· 1 shared Jakub VohryzekiD· 1 shared Jean‐Charles DelvenneiD· 1 shared Kim Q.iD· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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2 shared papersNeuroscience

Patric HagmannORCID

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2 papers

Recent·Most cited

Brain network connectivity underlying remission in early psychosis: a whole brain model approach

Ludovica Mana, Ane López‐González, Yasser Alemán‐Gómez, Philipp Baumann, Raoul Jenni, Luis Alameda, Lilith Abrahamyan Empson, Paul Klauser, Philippe Conus, Patric Hagmann, Manel Vila‐Vidal, Gustavo Deco

This study uses whole-brain models to analyze brain connectivity differences between remitting and non-remitting early psychosis patients, finding altered functional connectivity and potential compensatory mechanisms.

Nature Mental Health · Mar 27, 2025Peer-reviewedNeuroscience

Stable Biomarker Identification For Predicting Schizophrenia in the Human Connectome

Leonardo Gutiérrez-Gómez, Jakub Vohryzek, Benjamin Chiêm, Philipp Baumann, Philippe Conus, Kim Q., Patric Hagmann, Jean‐Charles Delvenne

This study identifies stable biomarkers for schizophrenia using machine learning on multi-modal connectome data, showing improved stability and accuracy through recursive feature elimination and support vector machines.

NeuroImage Clinical · Jan 1, 2020Peer-reviewedNeuroscience