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Cristian Inca

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Open access Aug 2026

Statistical Models and Machine Learning in Depression Detection: Evaluating XGBoost

The research compares the performance of XGBoost with traditional logistic regression and decision tree approaches for identifying and predicting depression and argues that XGBoost has the potential to improve current diagnostic practices by reducing current time and costs.

María Barrera, Cristian Inca, Zilma Diago et al. · 0 citations

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