Machine learning classification of patients after suicide attempts using demographic data, EEG connectivity and heart rate variability.

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Bibliographic Details
Title: Machine learning classification of patients after suicide attempts using demographic data, EEG connectivity and heart rate variability.
Authors: Pribis M; University of Zurich, Psychiatric University Hospital Zurich, Department of Psychiatry, Psychotherapy and Psychosomatics, Zurich, Switzerland. Electronic address: matej.pribis@pukzh.ch., Bankwitz A; University of Zurich, Psychiatric University Hospital Zurich, Department of Psychiatry, Psychotherapy and Psychosomatics, Zurich, Switzerland., Gyurkó DM; Neurocenter, Luzerner Kantonsspital, Lucerne, Switzerland., Olbrich S; University of Zurich, Psychiatric University Hospital Zurich, Department of Psychiatry, Psychotherapy and Psychosomatics, Zurich, Switzerland.
Source: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology [Clin Neurophysiol] 2026 Aug; Vol. 188, pp. 2111904. Date of Electronic Publication: 2026 Apr 26.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 100883319 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-8952 (Electronic) Linking ISSN: 13882457 NLM ISO Abbreviation: Clin Neurophysiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1872-8952
DOI:10.1016/j.clinph.2026.2111904