Machine Learning-Based Clinical Decision Support System for Suicide Risk Management: The PERMANENS Project

Angela Leis; Philippe Mortier; Franco Amigo; Madhav Bhargav; Susana Conde; Montserrat Ferrer; Oskar Flygare; Busenur Kizilaslan; Laura Latorre Moreno; Miguel Angel Mayer; Víctor Pérez Sola; Ana Portillo Van Diest; Juan Manuel Ramírez-Anguita; Ferran Sanz; Gemma Vilagut; Jordi Alonso; Lars Mehlum; Ella Arensman; Johan Bjureberg; Manuel Pastor; Ping Qin

doi:10.3233/SHTI250308

Machine Learning-Based Clinical Decision Support System for Suicide Risk Management: The PERMANENS Project

Angela Leis
, Philippe Mortier
, Franco Amigo
, Madhav Bhargav
, Susana Conde
, Montserrat Ferrer
, Oskar Flygare
, Busenur Kizilaslan
, Laura Latorre Moreno
, Miguel Angel Mayer
, Víctor Pérez Sola
, Ana Portillo Van Diest
, Juan Manuel Ramírez-Anguita
, Ferran Sanz
, Gemma Vilagut
, Jordi Alonso
, Lars Mehlum
, Ella Arensman
, Johan Bjureberg
, Manuel Pastor

Ping Qin

School of Public Health

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

Abstract

The PERMANENS European project addresses the global public health challenge of self-harm and suicide by developing a machine learning-based Clinical Decision Support System (CDSS) to assist emergency departments (EDs) in providing personalized care. With over 700,000 suicides annually, suicide prevention is critical, especially in Europe where consistent surveillance is lacking. The project harmonizes national suicide attempt registries from regions in Spain, Ireland, Norway, and Sweden using the OMOP Common Data Model (CDM) to create a comprehensive database for real-time analysis.

Original language	English
Title of host publication	Studies in Health Technology and Informatics
Pages	221-222
Number of pages	2
DOIs	https://doi.org/10.3233/SHTI250308
Publication status	Published - 15 May 2025
Event	35th Medical Informatics Europe Conference, MIE 2025 - Glasgow, United Kingdom Duration: 19 May 2025 → 21 May 2025

Conference

Conference	35th Medical Informatics Europe Conference, MIE 2025
Country/Territory	United Kingdom
City	Glasgow
Period	19/05/25 → 21/05/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

clinical support system
machine learning
self-harm
Suicide

Access to Document

10.3233/SHTI250308

Cite this

Leis, A., Mortier, P., Amigo, F., Bhargav, M., Conde, S., Ferrer, M., Flygare, O., Kizilaslan, B., Latorre Moreno, L., Mayer, M. A., Pérez Sola, V., Portillo Van Diest, A., Ramírez-Anguita, J. M., Sanz, F., Vilagut, G., Alonso, J., Mehlum, L., Arensman, E., Bjureberg, J., ... Qin, P. (2025). Machine Learning-Based Clinical Decision Support System for Suicide Risk Management: The PERMANENS Project. In Studies in Health Technology and Informatics (pp. 221-222) https://doi.org/10.3233/SHTI250308

@inproceedings{1151d94e12f44ceeb42721798edd4584,

title = "Machine Learning-Based Clinical Decision Support System for Suicide Risk Management: The PERMANENS Project",

abstract = "The PERMANENS European project addresses the global public health challenge of self-harm and suicide by developing a machine learning-based Clinical Decision Support System (CDSS) to assist emergency departments (EDs) in providing personalized care. With over 700,000 suicides annually, suicide prevention is critical, especially in Europe where consistent surveillance is lacking. The project harmonizes national suicide attempt registries from regions in Spain, Ireland, Norway, and Sweden using the OMOP Common Data Model (CDM) to create a comprehensive database for real-time analysis.",

keywords = "clinical support system, machine learning, self-harm, Suicide",

author = "Angela Leis and Philippe Mortier and Franco Amigo and Madhav Bhargav and Susana Conde and Montserrat Ferrer and Oskar Flygare and Busenur Kizilaslan and \{Latorre Moreno\}, Laura and Mayer, \{Miguel Angel\} and \{P{\'e}rez Sola\}, V{\'i}ctor and \{Portillo Van Diest\}, Ana and Ram{\'i}rez-Anguita, \{Juan Manuel\} and Ferran Sanz and Gemma Vilagut and Jordi Alonso and Lars Mehlum and Ella Arensman and Johan Bjureberg and Manuel Pastor and Ping Qin",

note = "Publisher Copyright: {\textcopyright} 2025 The Authors.; 35th Medical Informatics Europe Conference, MIE 2025 ; Conference date: 19-05-2025 Through 21-05-2025",

year = "2025",

month = may,

day = "15",

doi = "10.3233/SHTI250308",

language = "English",

pages = "221--222",

booktitle = "Studies in Health Technology and Informatics",

}

Leis, A, Mortier, P, Amigo, F, Bhargav, M, Conde, S, Ferrer, M, Flygare, O, Kizilaslan, B, Latorre Moreno, L, Mayer, MA, Pérez Sola, V, Portillo Van Diest, A, Ramírez-Anguita, JM, Sanz, F, Vilagut, G, Alonso, J, Mehlum, L, Arensman, E, Bjureberg, J, Pastor, M & Qin, P 2025, Machine Learning-Based Clinical Decision Support System for Suicide Risk Management: The PERMANENS Project. in Studies in Health Technology and Informatics. pp. 221-222, 35th Medical Informatics Europe Conference, MIE 2025, Glasgow, United Kingdom, 19/05/25. https://doi.org/10.3233/SHTI250308

TY - GEN

T1 - Machine Learning-Based Clinical Decision Support System for Suicide Risk Management

T2 - 35th Medical Informatics Europe Conference, MIE 2025

AU - Leis, Angela

AU - Mortier, Philippe

AU - Amigo, Franco

AU - Bhargav, Madhav

AU - Conde, Susana

AU - Ferrer, Montserrat

AU - Flygare, Oskar

AU - Kizilaslan, Busenur

AU - Latorre Moreno, Laura

AU - Mayer, Miguel Angel

AU - Pérez Sola, Víctor

AU - Portillo Van Diest, Ana

AU - Ramírez-Anguita, Juan Manuel

AU - Sanz, Ferran

AU - Vilagut, Gemma

AU - Alonso, Jordi

AU - Mehlum, Lars

AU - Arensman, Ella

AU - Bjureberg, Johan

AU - Pastor, Manuel

AU - Qin, Ping

PY - 2025/5/15

Y1 - 2025/5/15

N2 - The PERMANENS European project addresses the global public health challenge of self-harm and suicide by developing a machine learning-based Clinical Decision Support System (CDSS) to assist emergency departments (EDs) in providing personalized care. With over 700,000 suicides annually, suicide prevention is critical, especially in Europe where consistent surveillance is lacking. The project harmonizes national suicide attempt registries from regions in Spain, Ireland, Norway, and Sweden using the OMOP Common Data Model (CDM) to create a comprehensive database for real-time analysis.

AB - The PERMANENS European project addresses the global public health challenge of self-harm and suicide by developing a machine learning-based Clinical Decision Support System (CDSS) to assist emergency departments (EDs) in providing personalized care. With over 700,000 suicides annually, suicide prevention is critical, especially in Europe where consistent surveillance is lacking. The project harmonizes national suicide attempt registries from regions in Spain, Ireland, Norway, and Sweden using the OMOP Common Data Model (CDM) to create a comprehensive database for real-time analysis.

KW - clinical support system

KW - machine learning

KW - self-harm

KW - Suicide

UR - https://www.scopus.com/pages/publications/105005817104

U2 - 10.3233/SHTI250308

DO - 10.3233/SHTI250308

M3 - Conference proceeding

C2 - 40380420

AN - SCOPUS:105005817104

SP - 221

EP - 222

BT - Studies in Health Technology and Informatics

Y2 - 19 May 2025 through 21 May 2025

ER -

Machine Learning-Based Clinical Decision Support System for Suicide Risk Management: The PERMANENS Project

Abstract

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this