• Vasanth Adithya Vadakattu
• Guru Sainath V
• Dr. D. Thamaraiselvi

Skin cancer is a form of cancer that can be extremely harmful. It is caused by DNA damage in skin cells that results in genetic mutations on the skin. If left untreated, skin cancer can spread to other parts of the body, which is why it is most effective to detect it in its earliest stages. The growing incidence of skin cancer, combined with its high mortality rate and costly medical treatments, highlights the importance of prompt diagnosis. To address these concerns, researchers have devised various early detection methods for skin cancer. These methods involve analyzing lesion characteristics such as color, size, shape, and symmetry to differentiate between benign and malignant skin cancer. Early detection is crucial in the fight against skin cancer, but manual diagnostic processes can be time-consuming and expensive. Fortunately, advancements in science and technology have made it possible to use machine learning, specifically convolutional neural networks, to detect cancerous cells more quickly and efficiently. This promises to revolutionize the way we approach the early detection and treatment of skin cancer.

Machine Learning, CNN, TensorFlow, Disease Detection, Neural Network, Deep Learning

"Skin Cancer Detection using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.f1-f6, May-2023, Available :http://www.jetir.org/papers/JETIR2305504.pdf

"Skin Cancer Detection using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppf1-f6, May-2023, Available at : http://www.jetir.org/papers/JETIR2305504.pdf