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@article{194129,
        author = {Vaidehi Ahire and Diksha Ashtekar and Samiksha Chhallani and Vardhman Chaudhari},
        title = {Design an AI based web application for early Skin Cancer Detection System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {5336-5345},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194129},
        abstract = {Skin cancer has become one of the fastest-growing cancers globally, especially due to increasing exposure to ultraviolet radiation and lifestyle factors. Accurate and early detection is crucial for patient survival and reducing mortality rates. Conventional methods of diagnosis depend heavily on dermatologists’ expertise and invasive biopsies, which are time-consuming and subject to human interpretation. Artificial Intelligence (AI) has emerged as a transformative technology capable of performing image-based skin lesion analysis, classification, and prediction with remarkable accuracy.
This survey paper comprehensively reviews AI-based approaches for skin cancer detection, emphasizing deep learning and machine learning models, preprocessing techniques, datasets, evaluation metrics, and emerging challenges. The study highlights the latest advancements, compares different model architectures, and discusses future research directions.},
        keywords = {Skin Cancer, Artificial Intelligence, Deep Learning, Machine Learning, CNN, Image Processing, Melanoma Detection, Medical Imaging.},
        month = {March},
        }