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Skin Cancer Detection: A Survey

Bhavay Khatri

Heera Lal Public School, Delhi

Vol: 13, Issue: 1, 2023

Receiving Date: 2022-11-13 Acceptance Date:

2022-12-28

Publication Date:

2023-01-05

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http://doi.org/10.37648/ijrst.v13i01.001

Abstract

Due to a lack of awareness of its warning signs and preventative measures, skin cancer—one of the deadliest types of cancer—has seen a significant increase in mortality rates. Therefore, early detection at an early stage is essential to halting the spread of cancer. Although there are other types of skin cancer, melanoma is the most dangerous. However, melanoma patients have a 96% survival rate when detected early with straightforward and cost-effective treatments. The project aims to classify various kinds of skin cancer using image processing and machine learning. Melanoma is a type of skin cancer that can be fatal. If detected early, melanoma skin cancer can be completely treated. Because it directly correlates with death, early melanoma skin cancer detection is critical for patients. In this study, early melanoma skin cancer is detected and categorized using a variety of algorithms, including K-means clustering, neural networks, K-Nearest Neighbour, and Naive Bayes.

Keywords: skin cancer; Melanoma; neural network

References

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