Enhanced Multimodal Fusion Framework for Robust Skin Disease Classification – A Systematic Review

: Skin diseases are among the most prevalent health conditions worldwide, requiring early and accurate diagnosis to prevent complications. Recent advancements in Artificial Intelligence, particularly Machine Learning, have enabled automated systems for skin disease classification using medical images. This paper presents a comprehensive approach to classifying skin diseases by leveraging convolution machine learning trained on dermoscopic and clinical image datasets. The proposed model improves the diagnostic accuracy by incorporating data augmentation and optimized feature extraction techniques. Experimental results demonstrate that the system achieves high accuracy and robustness across multiple skin disease categories. The study highlights the potential of AI-assisted diagnostic tools in Dermatology, especially in improving access to healthcare in resource-limited settings.