Colorectal cancer (CRC) is a significant public health concern worldwide, known for its impact on morbidity and mortality. Based on the most recent GLOBOCAN 2020 data collected from 185 countries by the International Agency for Research on Cancer (IARC), CRC is the 3rd most commonly diagnosed cancer globally, with 1,930,000 cases, and it ranks 2nd in terms of mortality with 935,000 deaths (1).

Despite advances in surgical techniques and adjuvant therapies, the specter of cancer recurrence looms large, necessitating the development of innovative strategies for early detection and intervention 2, 3, 4.

In this era of transformative technological advancements, the integration of machine learning into the domain of oncology holds the promise of revolutionizing our approach to cancer care. 5, 6, 7.

CRC, often diagnosed at advanced stages, underscores the urgency of identifying patients at heightened risk of recurrence following surgical resection. Among newly diagnosed cases of CRC, 20% of patients are initially diagnosed with metastatic disease, and an additional 25% of those initially diagnosed with localized disease will eventually develop metastases (8).

Recurrence, a complex and multifactorial phenomenon, demands a proactive and precision-driven approach to ensure timely therapeutic interventions and improved patient outcomes.

Machine learning, a subfield of artificial intelligence, has emerged as a powerful tool in healthcare, capable of discerning intricate patterns within vast datasets and informing clinical decision-making 9, 10, 11.

This article delves into the utilization of machine learning algorithms to predict the recurrence of colon cancer (CC) in patients who have undergone surgical resection. Such predictive models have the potential to usher in a new era of personalized postoperative care, augmenting the physician's armamentarium with data-driven insights.

The pursuit of precision medicine for CC recurrence prediction not only has the potential to improve patient outcomes but also stands as a testament to the synergy between medical expertise and cutting-edge technology in the fight against cancer.