Abstract: Health is the most valuable factor affecting our life. People are highly focused on the health care with high preference. Now-a-days there are so many fatal diseases occurring in individuals, Cancer is one of those fatal diseases which is the cause of death of the several peoples in a year and in those people, breast cancer is a major cause of women death. According to the recent survey, about 1 in 8 women (about 12 percent) have breast cancer. Diagnosis of disease is usually done in the last stage and hence cannot be cured by treatment. Early diagnosis of this disease is essential and which needs regular check-up should be done by women above 40 years of age. This paper provides a methodology for automatic diagnosis of disease which is more feasible to be used by the individual person, caretaker, friends and family members which is more feasible. A system analyses patient's biomedical data and find out an existence of breast cancer in the patient. The genetic algorithm Olex GA used to classify patient in different stages as per her symptoms and test reports. The genetic Olex algorithm is a text-based classification algorithm. The visual report of diagnosis is generated which is easy to be understood by an individual from non-medical background. Also, one more feature of this system is the adaptation. New symptoms ant tests are saved in a database and those will train manually. This approach helps the patients, doctors and family members to find out.
Keywords: Text based classification, Data Mining, Supervised learning, Olex GA.