The Identification and Classification of Rash Conditions Compared to Skin Cancer
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International Journals of Sciences and High Technologies
Abstract
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When left untreated, skin cancer can quickly spread throughout the human body. To a Dermatologist, skin cancer and rashes may look the same. Therefore, distinguishing between rashes and skin cancer might be challenging. People and medical professionals alike use the term "rash" to refer to any visible alteration in the skin, including but not limited to an infection, an allergic reaction, or a disease. A dermatologist will suspect skin cancer from a rash if it does not improve after several weeks of treatment and if it quickly spreads to other areas of the body. Meanwhile, being aware of the distinctions between rashes and skin cancer might assist a person decide whether to seek medical attention or relax about a rash that is not dangerous. The purpose of this study is to aid in the early detection of skin cancer by clarifying the differences between skin cancer and rashes. Image classification has been used well in previous research to distinguish between different forms of skin cancer. This model uses a Convolutional Neural Network (CNN) to recognise and distinguish between skin cancer and rash photos. With an average accuracy of 80.2%, the model determined whether the image depicted skin cancer or a rash.
Keywords
Image Classification, Image processing, Convolutional Neural Network, Deep learning