Title: Colorectal cancer risk factor assessment in Palestine using machine learning models

Authors: Mohammad A.Z. Abu Zuhri; Mohammed Awad; Shahnaz Najjar; Nuha El Sharif; Issa Ghrouz

Addresses: Department of Nursing, Arab American University, Palestine ' Department of Computer Systems Engineering, Arab American University, Palestine ' Department of Health Informatics, Arab American University, Palestine ' Faculty of Public Health, AlQuds University, Palestine ' Ministry of Health, Ramallah, Palestine

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, and 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.

Keywords: colorectal cancer; CRC; data mining; risk factors; machine learning; classification; Palestine.

DOI: 10.1504/IJMEI.2024.136963

International Journal of Medical Engineering and Informatics, 2024 Vol.16 No.2, pp.126 - 138

Received: 19 Jul 2021
Accepted: 07 Nov 2021
Published online: 01 Mar 2024 *

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