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Volume 12, Issue 4 (April 2026)

An Intelligent Multi-algorithm Machine Learning System For Skin Disease Classification And Prediction

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7.883
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Volume 12 Issue 07

July 2026

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Author(s)

M.Gughan Raja S.Afreen Reikhana S.jeya Varshini

Abstract

This Paper Proposes An Interpretable And Explainable Multi-class Skin Lesion Classification Model For The HAM10000 Dataset. Timely Detection Of Skin Cancer Is Important But Difficult Due To Class Imbalance And Uninterpretability Of Current Models. The Model Employs EfficientNetV2-L With Channel Attention For Improved Feature Extraction And Classification. An Effective Preprocessing Strategy With Data Augmentation And Smart Class Balancing Is Used. Progressive Training In Three Stages Enhances Generalization. Visual Explainable AI, Including Grad-CAM And Saliency Maps, Explains Predictions Visually. The Model Has 91.15% Accuracy And 99.33% AUC Across Seven Classes. The Solution Enhances Diagnostic Performance And Interpretability, Enabling Its Use As A Decision Support System.

Keywords

Skin Cancer Detection Deep Learning Dermatoscopic Image Classification And Transfer Learning Grad-CAM Saliency Maps Data Augmentation Class Imbalance Handling And HAM10000 Dataset

Paper ID

IJSARTV12I4105213

Publication Date

April 30, 2026

Research Area

Artificial Intelligence And Data Science

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