Author

Shahid Mohammad Ganie

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Open access Sep 2026

Lung cancer risk prediction using interpretable ensemble models on lifestyle and clinical data

The results suggest that stacking-based ensembles can improve risk prediction from lifestyle and clinical indicators while maintaining model transparency through SHAP and LIME explanations, highlighting the potential of interpretable ensemble learning as a decision-support tool for lung cancer risk assessment.

Shahid Mohammad Ganie, P. K. Dutta Pramanik, Zhong-Ming Zhao · PLoS ONE · 0 citations

Open access Sep 2026

Explainable ensemble learning framework with recursive feature elimination for lung cancer stage prediction using demographic and lifestyle parameters

The proposed explainable ensemble learning framework provides accurate, robust, and interpretable lung cancer stage prediction through the integration of leakage-free model development, optimized ensemble learning, explainable artificial intelligence, statistical validation, and component-wise ablation analysis.

M. Alfuraydan, Shahid Mohammad Ganie, Ehab Seedahmed et al. · Discover Computing · 0 citations