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Author

Kamal Upreti

2 papers indexed here

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Open access Oct 2026

An interpretable feature-augmented stacked ensemble framework for student dropout prediction

Student dropout prediction is regarded as one of the significant research fields in educational data mining. It aids the sustainability of institutions and early interventions in schools. This study proposes an Enhanced Stacked Dropout Predictor (eSDP), which is a feature-enhanced hybrid stacking framework. The propose...

Rituraj Jain, Nay Lwin, Ah Maung Oo et al. · 0 citations
Open access Sep 2026

A Clinical Engineering-Oriented Explainable Artificial Intelligence Framework for Chronic Kidney Disease Risk Estimation and Multi-Parameter Staging

Background/objectives: Chronic kidney disease (CKD) is a progressive and often asymptomatic disorder that requires early detection supported by interpretable clinical decision systems. Conventional machine-learning (ML) models provide strong predictive accuracy but frequently lack physiological transparency and clinica...

M. Kaur, Parul Gandhi, Kamal Upreti · 0 citations

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