International Journal of Advanced Innovative Technology in Engineering (IJAITE)

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Early Detection of Skin Cancer Using Machine Learning

Aafreen Akhtari, Abhishek Raibole, Chetan Badge, Kaustubh Wankhede, Sahbaz Khan, Sadia Patka

Abstract :

Nowadays we are facing many kinds of diseases and in which melanoma cancer is the most dangerous one. It has made lakhs of deaths people and it can happen to anyone. And this is drastically increasing due to a lack of knowledge on the symptom and prevention. Therefore, it has become very necessary to detect it at a premature stage. and again, this skin cancer is divided into various types of melanomas which is very harmful, Basal cell carcinoma, and Squamous cell carcinoma. The project is all about the detection of skin cancer using machine learning. In the pre-processing stage, we are considering a dermoscopic image as input, the razor is used to remove unwanted hairs from the image. Gaussian filter is used for smoothening images since the color is also an important feature in analyzing the type of cancer k means clustering is performed in the segmentation phase. The statistical and texture feature extraction is implemented using Asymmetry, Border, Color, Diameter, (ABCD), and Gray Level Co-occurrence Matrix (GLCM). The experimental analysis is done on the dataset and the classification purpose, Support Vector Machine (SVM) was implemented and the accuracy obtained is good and we have used the KNN algorithm also for classification purposes.

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