Tahir, AnooshaWajid, BilalAnwar, FariaAwan, Fahim GoharRashid, UmarAfzal, FareehaAnwar, Abdul RaufWajid, Imran2023-11-132023-11-132023https://hdl.handle.net/11467/7003https://doi.org/10.1109/ICEPECC57281.2023.10209530Knowledge of survivability is crucial for cancer patients and their families. This paper employs the Surveillance, Epidemiology, and End Results (SEER) database to predict the survivability of colon cancer patients. The research presents four experiments each improving over the previous one, attempting to develop the optimal model. Here (i) experiment 1 conducts regression analyses; (ii) experiment 2 conducts multinomial classification; (iii) experiment 3 emphasizes a multi-tier prediction framework and lastly; (iv) experiment 4 concludes by developing a hybrid model for better prediction of survivability.eninfo:eu-repo/semantics/embargoedAccesscolon cancer, machine learning, survival rate, SEERConference ObjectN/A2-s2.0-8516960196810.1109/ICEPECC57281.2023.10209530