Author

NE. Sravani

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Open access Aug 2026

Multi-paradigm Vision Transformer ensemble with regional attention and MLP meta-fusion for explainable dermoscopic skin lesion classification

An exhaustive explainability framework comprising Regional Attention Maps, GradCAM++, SHAP, and t-SNE provides complementary spatial, gradient-based, pixel-level, and embedding-level interpretability, ensuring clinical trust, transparency, and trustworthiness expected from an automated dermoscopy system.

NE. Sravani, Srinivas Koppu · Frontiers in Medicine · 0 citations

#explainable ai Open access Sep 2026

Explainable ensemble transfer learning for skin lesion classification with multi-method explainability validation

Quantitative evaluation using TMAI and complementary XAI methods provides additional evidence that the model's predictions are grounded in clinically relevant lesion regions rather than background artefacts, supporting the potential of the framework for accurate and interpretable automated skin lesion classification.

NE. Sravani, Srinivas Koppu · Frontiers in Public Health · 0 citations