Explainable Machine Learning for Suicide Risk Assessment Using Social Media Data

Accurate and interpretable suicide risk assessment is critical for timely intervention in mental health contexts. This study presents an explainable machine learning approach for suicide risk assessment using social media data, evaluating both multi-class and binary classification settings alongside...

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Bibliografiska uppgifter

Huvudupphov:	Tsholofelo Mokheleli, Tebogo Makaba, Patrick Ndayizigamiye, Nompumelelo Ndlovu, Hossana Twinomurinzi
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	IEEE 2026-01-01
Serie:	IEEE Access
Ämnen:	Explainable AI suicide risk assessment social media natural language processing SHAP LIME
Länkar:	https://ieeexplore.ieee.org/document/11523010/
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