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Patient complexity profiles in depression

A machine learning approach to personalized mental health

Bibliographic Data

ID15526212
AuthorsPaula Dagnino (0000-0002-4923-9827, San Sebastián University, corresponding author), Matías Salinas (0000-0002-5548-2997, Valparaiso University), Rodrigo Salas (0000-0002-0350-6811, Valparaiso University)
Year2026
Volume17
Pages1741860-1741860
Publication date2026-02-10
Open AccessYes
TypeARTICLE
VenueFrontiers in Psychiatry (JOURNAL)
Journal identifiersISSN: 1664-0640 • E-ISSN: 1664-0640
PublisherFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2026.1741860
PMID41743038
OpenAlexW7128536125
LanguageFR
References cited51

Machine learning identified clinically meaningful patient complexity profiles with significant differences across multiple domains. These profiles provide a framework for stratified care and personalized intervention planning, moving beyond one-size-fits-all approaches

Deep learning · Health care · Intervention (counseling · Meaningful use · Mental health · Patient care · Personalized medicine · Digital Mental Health Interventions · Machine Learning in Healthcare · Treatment of Major Depression

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