Melanoma Skin Cancer Detection Using Improved RBF Classifier - Thenmozhi, K (International Journal of Computer Sciences and Engineering, 2025)
Melanoma is a category of cancer that develops from the pigment-containing cells recognized as melanocytes. Melanomas usually ensue in the fur but may arise in the jaws, guts or ogle. This paper tends to two distinct frameworks for identification of skin growth in dermoscopy pictures. The primary framework utilizes worldwide strategies and the second framework utilizes neighborhood highlights and the classifier. Henceforth, melanoma is effortlessly to distinguish utilizing with help of worldwide strategies and neighborhood highlights. Skin Disease prediction has become important in a variety of applications such as health insurance, tailored health communication and public health. Due to the costs for dermatologists to monitor every patient, there is a need for an computerized system to evaluate a patient’s risk of melanoma using images of their skin lesions captured using a standard digital camera. The traditional diagnosis technique aims at improving the quality of existing diagnostic systems by proposing advanced feature selection and classification methods.RBF neural network derives classification. For this classification (RBF neural network)this paper proposed new learning method using K means clustering. This paper focuses on the detection of skin lesion as a literature survey