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