Author

Eric G.A.L Van Diessen

University Medical Center UtrechtORCID 0000-0002-7773-1990Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 3

Signature Assays, Organisms & Methods

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Assay:electronic health records· 3 Organism:human· 3 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Willem M. OtteiD· 3 shared Frank van der Maas· 2 shared Jan W. Buitenhuis· 2 shared Michel R.T. SinkeiD· 2 shared Floor E. JanseniD· 1 shared Geertruida SlingeriD· 1 shared Job Nwiboko· 1 shared Kees P. J. BrauniD· 1 shared

Activity by Year

2018-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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3 shared papersNeuroscience

Willem M. OtteORCID

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3 papers

Recent·Most cited

The etiological classification of the epilepsies: A brain network underpinning?

Geertruida Slinger, Willem M. Otte, Lotte Noorlag, Floor E. Jansen, Kees P. J. Braun, Eric G.A.L Van Diessen

This study investigates whether epilepsy etiology is associated with brain network topology but finds no such correlation.

bioRxiv · Aug 19, 2019 · PreprintNeuroscience

The power of language: functional brain network topology of deaf and hearing in relation to sign language experience

Michel R.T. Sinke, Jan W. Buitenhuis, Frank van der Maas, Job Nwiboko, Rick M. Dijkhuizen, Eric G.A.L Van Diessen, Willem M. Otte

This study compares functional brain network shifts between deaf and hearing individuals, finding increased auditory-visual connectivity and network backbone changes in deaf people related to sign language experience.

Hearing Research · Dec 15, 2018Peer-reviewedNeuroscience

Reliable and automatic epilepsy classification with affordable, consumer-grade electroencephalography in rural sub-Saharan Africa

Vincent T. van Hees, Eric G.A.L Van Diessen, Michel R.T. Sinke, Jan W. Buitenhuis, Frank van der Maas, Lars Ridder, Willem M. Otte

This study uses low-cost consumer-grade EEG and machine learning to classify epilepsy in rural settings, achieving moderate cross-country performance.

bioRxiv · May 17, 2018 · PreprintNeuroscience