Cancer Detection is still challenging for the upgraded and modern medical technology. Evan now the actual reason and total curing procedure of cancer is not invented .After researching a lot statistical analysis which is based on those people whose are affected in brain cancer some general Risk factors and Symptoms have been discovered. The development of technology in science day night tries to develop new methods of treatment. According to a developing country like Bangladesh it is very difficult to bear hug amount of cost for treatment of brain cancer. But it is very easy to protest brain cancer before affected and reduce treatment cost. But the number of brain cancer patients is increasing rapidly in Bangladesh lack of education, money and consciousness. Dreadful, costly and fatal brain cancer also depends on some factors that are known risk factors of brain cancer like other cancers. The detection of Skin Cancer from some important risk factors is a multi-layered problem. Initially according to those risk factors 150 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 Brain Cancer. Next significant frequent patterns are discovered using Pattern Decomposition algorithm shown in Table 1. Finally implement a system using java to predict Brain Cancer risk level which is easier, cost reducible and time saveable.
The upgraded and modern medical technologies are the most challenging task to detect cancer and provide accurate treatment. In Bangladesh about two million women are affected by 2 nd most occurring deathful breast cancer due to them and their family member's unconsciousness and poverty. It requires about $400-500 for proper diagnosis and treatment. Most of the Bangladeshi women are uneducated and feel shy with society or husband to go doctor for checking breast cancer. So it also will be a good achievement of this work to find breast cancer with more efficiency. Breast cancer depends on some risk factors that may help to detect breast cancer using multi-layered approach. In this work, at first it is collected 100 peoples' information which consist of both cancer and non-cancer information having missing or duplicate information. So pre-processing and K-means clustering methods are performed to separate relevant and non-relevant data to Breast Cancer. Then risk factors are ranked using WEKA tools and are assigned a score according to rank. Finally, it is implemented an application software using Lotus Notes to predict Breast Cancer risk level which is easier, effective, efficient, secured, cheap and time saving with some suggestions. This technique will contribute equal opportunity to the underdeveloped and developing countries to detect, diagnosis, and treatment of breast cancer. General TermsComputer Science, Data Mining, Breast Cancer in Bangladesh KeywordsBreast cancer in Bangladesh, Public health, Data mining, Risk factors of breast cancer, WEKA toolkit, Woman Health Conditions
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