Diagnostic accuracy of machine learning approaches for suicide‑related outcomes: a meta‑analysis

Abstract Objective This diagnostic test accuracy meta-analysis aimed to provide clinically interpretable estimates (sensitivity, specificity, likelihood ratios (LR), predictive value (PV) and post‑test probabilities) for machine‑learning (ML) models predicting suicide‑related outcomes. Methods A sys...

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Autori principali:	Parisa Kohnepoushi, Maryam Afraie, Hamza Rahmani, Seyedeh Asrin Seyedoshohadaei, Babak Ghadirzadeh, Yousef Moradi
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	BMC 2026-05-01
Serie:	Annals of General Psychiatry
Soggetti:	Machine learning Suicidal ideation Suicide attempts Suicide mortality Diagnostic accuracy Meta-analysis
Accesso online:	https://doi.org/10.1186/s12991-026-00671-4
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