(Sk)2: Saadaali Salamti fi Kidney Kanceri – predicting survivability of kidney cancer using a multi – tier classification framework

Kidney cancer is known as one of the deadliest cancers, with high morbidity and mortality rate. Survivability from cancers is always the patient's first concern. Thus, methods need to be devised to find the survivability rate. To achieve this goal, machine learning models are effective at providing aid to clinicians because of their accuracy. In this research paper SEER (Surveillance, Epidemiology, and End Results) database was used to provide information on cancer statistics. Three different approaches were used in this paper. The first experiment used regression models, the second included multi-class classification models to predict the survivability rate, and the third used multi-tier classification. In the end, we achieved 71% accuracy through our models to predict the survivability of a patient