Cervical Cancer Test Identification Classifier using Decision Tree Method
Dipti N. Punjani, Kishor Atkotiya · International Journal of Research in Advent Technology · 2019
Cervical cancer is one of the most crucial and important type of cancers which needs to be treated as early as possible.The most difficult task is to detect a cancer at early stage so that necessary cure can be done on time.Several medical research works have been done towards the various medical tests which cervical cancer patients should go for.The four most frequent tests are: hinselmann, schiller, citology, and biopsy.These four tests might be expensive to afford all at a time.This research work focuses on prediction of which test a patient should go first for cervical cancer identification.a real dataset of approx.800 patients of hospital universitario de caracas' in caracas, venezuel is used for the training purpose.Decision tree method is used to build a classifier.