Abstract
World Health Organization reports cancer as a leading cause worldwide in mortality and morbidity. Accurate and early cancer risk assessment in average- to high-risk population is vital in controlling the cancer-related suffering and mortality. Advanced bioinformatics and data mining techniques along with computer-aided cancer prediction and risk assessment are used extensively to assist in identifying the high-risk population as well as individual cancer diagnosis and treatment. An early detection minimizes the risk of cancer spreading to secondary sites and ensures appropriate treatment at the onset of the malignancy. The scope of our survey was to review over 90 publications centered around works done in the area of data analysis studies in the field of cancer prediction and detection. The motivation was to accumulate and categorize knowledge on the usage of data analytics for cancer prediction and detection. The aim was to do a comparative study of few of the major analytical approaches in cancer data analysis and highlight their effectiveness.
