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An Explainable Machine Learning Framework for Early Mental Health Risk Detection among University Students in Fragile and Conflict-Affected Settings

Ahmed Ashlam Muner Athaba C E Mr Abdelatti Blg
· 0 citations · 2 references

TL;DR

An explainable machine-learning framework for early mental health risk stratification among university students in FCAS contexts is developed that combines demographic, academic, socioeconomic, psychological, and contextual indicators within a structured modelling pipeline designed to support transparency, calibration, and practical decision-making.

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