Published Paper Details:

Cancer is a major cause of death. An estimated 1,735,350 new cases of cancer were diagnosed in US alone in the year 2018 and 609,640 people died due to the illness. There are various kinds of cancer like melanoma of skin, lung bronchus cancer, breast cancer, prostate cancer, colon and rectum cancer, bladder cancer, kidney and renal pelvis cancer etc. With these many different types of cancer present and large number of affected population, cancer has gained popularity in the research field. Till date, novel methods for prevention and diagnosis of cancer are being continuously researched on. We have aimed to develop a robust and viable system for cancer detection using data mining techniques. This Cancer Disease Prediction application is an end user support and online consultation project. It makes use of multi-layer data mining techniques such as clustering and decision tree technique to build a novel application. The proposed model, is an intelligent online system that relies on the various details of cancer disease which are pre-fed to the application. Based on these details an instant guidance is offered on the progression of the disease. The users are allowed to input their specific health related information, obtaining the data, the application uses pre-fed information to predict the potential cause of the symptoms using data mining techniques. Thus, the developed prediction system warns the users for potential diseases based on their current medical information and is also cost-effective, hence, offering dual benefits.