TY  - JOUR
TI  - Automatic Tool for Prediction of Type of Cancer Risk and Recommendations
AU  - Pallavi Mirajkar
AU  -  Dr. G. Prasanna Lakshmi
AU  -  Dr. Ritu Khanna
JO  - International Journal of Scientific Research in Computer Science, Engineering and Information Technology
PB  - Technoscience Academy
DA  - 2019/01/30
PY  - 2019
DO  - https://doi.org/10.32628/CSEIT1838116
UR  - https://ijsrcseit.com/CSEIT1838116
VL  - 5
IS  - 1
SP  - 01	
EP  - 08
AB  - 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.