The development of human neoplasms can be provoked by exposure to one of several viruses. Burkitt lymphoma, cervical carcinoma, and hepatocellular carcinoma are associated with Epstein-Barr, human papilloma, and hepatitis B virus infections, respectively. Over the past three decades, many studies have attempted to establish an association between colorectal cancer and viruses, with debatable results. The aim of the present research was to assess the presence of BK polyomavirus (BKV) DNA and protein in colorectal cancer samples from patients in the Western Province of Saudi Arabia.
We evaluated the application of three machine learning algorithms, including logistic regression, support vector machine and back-propagation neural network, for diagnosing congenital heart disease and colorectal cancer. By inspecting related serum tumor marker levels in colorectal cancer patients and healthy subjects, early diagnosis models for colorectal cancer were built using three machine learning algorithms to assess their corresponding diagnostic values.