Author

Christoph Kellinghaus

Klinikum OsnabrückORCID 0000-0001-5491-2302Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Ayşegül GüveniD· 1 shared Carsten Hermann WoltersiD· 1 shared Daniela CzernochowskiiD· 1 shared Demet Yeşi̇lbaşiD· 1 shared Gabriel MöddeliD· 1 shared Lala JafarovaiD· 1 shared Sebastian SägeriD· 1 shared Stefan RamppiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperNeuroscience

Ayşegül GüvenORCID

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1 paper

Recent·Most cited

NeurosciencebioRxivPreprintMar 10, 2026

Machine-Learning-Based spike marking in signal and source space EEG from a patient with focal epilepsy

Lala Jafarova, Demet Yeşi̇lbaş, Christoph Kellinghaus…·Carsten Hermann Wolters

This paper uses artificial neural networks to classify interictal epileptiform discharges in EEG data from a patient with focal epilepsy, achieving high accuracy in signal and source space analyses.

DOI 10.64898/2026.03.06.710063

electronic health recordsmachine learning (classical)

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