CSEIT1838116 | Received : 28 Dec 2018 | Accepted : 03 Jan 2019 | January-February -2019 [ 5 (1) : 01-08 ] International Journal of Scientific Research in Computer Science, Engineering and Information Technology © 2019 IJSRCSEIT | Volume 5 | Issue 1 | ISSN : 2456-3307 DOI : https://doi.org/10.32628/CSEIT1838116 01 Automatic Tool for Prediction of Type of Cancer Risk and Recommendations Pallavi Mirajkar 1 , Dr. G. Prasanna Lakshmi 2 , Dr. Ritu Khanna 3 1 Research Scholar, Faculty of Computer Science, Pacific Academy of Higher Education and Research University, Udaipur, Rajasthan, India 2 (WOS-A) Andhra University, AU North Campus, Visakhapatnam, Andhra Pradesh, India 3 Professor & Head, Basic Science, Faculty of Engineering, Pacific University, Udaipur, Rajasthan, India ABSTRACT Cancer can begin in any part of the body and can spread to other parts also. It is uncontrollable and it has many types. In the proposed thesis research paper, a tool for prediction of type of cancer risk with five different cancer diagnosis and recommendations is presented. For recognizing cancer disease number of tests ought to be required from the patient. But using data mining techniques these test can be diminished. Indeed, an accurate prediction of cancer is very difficult task for medical practitioner and it is also high concern to the patients so that better treatment can be given and it will also increase the survival time of the patients. Our findings suggested that suitable prediction tool can effectively reduce the several tests for diagnosing cancer and prediction accuracy thereby increasing the technical possibility of early detection of cancer. The main features of the tool comprise a balance between the number of necessary inputs and prediction performance, being portable, and it empowers the automatic development of the cancer risk prediction tool in cancer disease. Keywords : Prediction Tool, Cancer, Data Mining, Automation, Integration. I. INTRODUCTION The rising high-performance computing has benefited numerous disciplines in finding realistic solutions to their issues. Our health services are no special case to this. Data mining tools have been created for useful investigation of medical information, to help oncologist in improving determination for treatment purposes. In cancer disease research, data mining technique have played out a noteworthy role. Cancer disease categorization contributes the unsafe reason for the treatment of patients. The aim of thesis work is to present an easy to use tool that provides predictions of cancer risk in patients or individual. Due to the internet facility available everywhere and the ease with which one is able to consult with proposed prediction tool, we chose to develop cancer prediction tool as an online system. Here the scope of the prediction tool is that integration of various risk factors that causes cancer, with computer-based patient records could reduce medical errors, enhance patient safety, improves the prediction of cancer risk in practice variation, and improve patient survival rate. The application is fed with different details to help medical practitioner to predict risk of type of cancer. The application permits user to share their health connected issues. It then processes user’s particular details to determine for varied cancer disease that might be related to it. Here we tend to utilize some intelligent data mining techniques to figure the correct risk level of cancer that may be