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Accepted manuscript

Indirect, Machine Learning-Based Suicide Risk Screening: Evidence from Cross-National Validation

Published online by Cambridge University Press:  13 February 2026

Polona Rus Prelog*
Affiliation:
University Psychiatric Clinic Ljubljana, Centre for Clinical Psychiatry, Ljubljana, Slovenia University of Ljubljana, Faculty of Medicine, Ljubljana, Slovenia
Martina Rojnic Kuzman
Affiliation:
Zagreb University Hospital Centre, Zagreb, Croatia Zagreb School of Medicine, Zagreb Croatia
Teodora Matić
Affiliation:
Artificial Intelligence Laboratory, University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia
Peter Pregelj
Affiliation:
University of Ljubljana, Faculty of Medicine, Ljubljana, Slovenia
Sara Medved
Affiliation:
Zagreb University Hospital Centre, Zagreb, Croatia
Sarah Bjedov
Affiliation:
Zagreb University Hospital Centre, Zagreb, Croatia
Irena Rojnic Palavra
Affiliation:
Psychiatric hospital Sveti Ivan, Zagreb Croatia
Anamarija Petek Eric
Affiliation:
University Hospital Centre Osijek, Psychiatry Clinic, J. Huttler 4, Osijek, Croatia Faculty of Medicine Osijek, University of Josip Juraj Strossmayer Osijek, Osijek, Croatia
Stipe Drmic
Affiliation:
Dubrava University Hospital, Zagreb Croatia Faculty of Health Sciences, University of Split
Domagoj Vidovic
Affiliation:
Vrapce Psychiatric University Hospital, Zagreb Croatia
Aleksander Sadikov
Affiliation:
Artificial Intelligence Laboratory, University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia
*
Author responsible for correspondence: Polona Rus Prelog, mailing address: University Psychiatric Clinic Ljubljana, Chengdujska 45, 1000 Ljubljana, Slovenia. Email: polona.rus@psih-klinika.si

Abstract

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Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of European Psychiatric Association
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