Furthermore, key factors influencing recurrence were identified and elucidated.<h4>Conclusion</h4>This study shows the transformative role of machine learning in recurrence prediction for CRC, particularly by investigating the minimum number of CEA measurements required for effective recurrence prediction. The gene discussed is CEACAM5; the disease is colorectal carcinoma.