Early Prevention and Detection of Skin Cancer Risk using Data Mining

Abstract

Till now Cancer is a big question for scientific community cause of no existing treatments could solve the problems related to this dreadful disease. Research is in well progress since half century but it failed to give an accurate solution to fight against it. The development of technology in science day night tries to develop new methods of treatment. One such mile stone treatment for cancer that is giving good hope to the people is cancer treatment based on genome sequencing. With respect to Bangladesh, Skin Cancer is a fatal, deadly, disabling and costly disease whose risk is increasing at alarming rate because of unconsciousness. Like other cancer Skin Cancer also depends on some factors that are known risk factors of skin cancer. So the detection of Skin Cancer from some important risk factors is a multi-layered problem. Initially according to those risk factors 200 people's data is obtained from different diagnostic centre which contains both cancer and non-cancer patients' information and collected data is pre-processed for duplicate and missing information. After pre-processing data is clustered using K-means clustering algorithm for separating relevant and non-relevant data to Skin Cancer. Next significant frequent patterns are discovered using MAFIA algorithm shown in Table 1. Finally implement a system using Lotus Notes to predict

Cite this paper

@inproceedings{Ahmed2013EarlyPA, title={Early Prevention and Detection of Skin Cancer Risk using Data Mining}, author={Kawsar Ahmed and Tasnuba Jesmin and Md. Zamilur Rahman and Hian Chye Koh and Gerald Tan and Quan Nguyen and Harry Zhang and Douglas Burdick and Manuel Calimlim and Zakaria Nouir and Berna Sayrac and Beno{\^i}t Fouresti{\'e} and Walid Tabbara and Françoise Brouaye}, year={2013} }