Krishanu Srium, Manav Shah, Dr. Santhi K
Vol. 21, Issue 1, Jan-Jun 2026
Abstract:
Skin diseases are a widespread health concern, impacting millions of people worldwide. Early and accurate diagnosis plays a vital role in effective treatment, yet traditional methods often depend on subjective clinical evaluations. In this research, we explore a deep learning-based approach to classifying skin diseases using transfer learning with the VGG16 model. By training the model on a diverse dataset covering nine categories of skin conditions, we employed advanced preprocessing techniques and data augmentation to boost its performance. The model achieved impressive classification accuracy, backed by strong metrics across multiple categories. This study highlights the transformative potential of artificial intelligence in dermatology, paving the way for improved accessibility, faster diagnoses, and enhanced patient care.
DOI: http://doi.org/10.37648/ijrmst.v21i01.003
Disclaimer: Indexing of published papers is subject to the evaluation and acceptance criteria of the respective indexing agencies. While we strive to maintain high academic and editorial standards, International Journal of Research in Medical Sciences and Technology does not guarantee the indexing of any published paper. Acceptance and inclusion in indexing databases are determined by the quality, originality, and relevance of the paper, and are at the sole discretion of the indexing bodies.