Colorectal cancer risk factor assessment in Palestine using machine learning models

Abstract

Colorectal cancer (CRC) has a prevalence of 15% among men and 14.6% among women of all cancers. This research was carried out to assess behavioural risk factors that affected Palestinian reported CRC cases, and to make use of machine learning (ML) tools that might be used in CRC prediction, where the use of a public CRC classification and prediction tool based on accurate ML tools might help individuals in addressing their behavioural CRC risk factors and enhancing their engagement with their health. In this research, Palestinian dataset that consists of 57 predictors was collected, the dataset consists of 216 instances. Statistical models were used to determine the important features. The study found that the most important risk factors to consider are age, past medical history, diet behaviours, physical activity, and obesity. Consequently, ML models were applied to classify and predict CRC risk factors. Results showed that ANNs outperformed all models