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

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.

Authors

Institutions

Publication Details

Journal
Studies in health technology and informatics
Published
2025-05-15
DOI
https://doi.org/10.3233/shti250308
Primary Topic
Healthcare Systems and Public Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Jordi Alonso, Montse Ferrer, Miguel Ángel Mayer, Lars Ivar Mehlum et al.
Studies in health technology and informatics
Healthcare Systems and Public Health
article

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

Jordi Alonso, Montse Ferrer, Miguel Ángel Mayer, Lars Ivar Mehlum, Franco Amigo, Ángela Leis, Madhav Bhargav, Víctor Pérez, Philippe Mortier, Juan Manuel Ramírez‐Anguita, Ferrán Sanz, Ping Qin, Manuel Pastor, Ella Arensman, Gemma Vilagut, Johan Bjureberg, Oskar Flygare, Susana Conde, Laura Latorre Moreno, Busenur Kizilaslan, Ana Portillo van Diest
article en

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.

Studies in health technology and informaticsVol. 327
Universitat Pompeu Fabra (ES), University of Oslo (NO), University College Cork (IE), Instituto de Salud Carlos III (ES), Karolinska Institutet (SE), Hospital Del Mar (ES), Parc de Salut (ES), National Suicide Research Foundation (IE), Stockholm Health Care Services (SE)
Good health and well-being
Openalex Percentile: Top 76%
Healthcare Systems and Public Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.