A new international study has found that using artificial intelligence (AI) in diagnosing colon cancer has led to big improvements in how quickly and accurately the disease can be detected.
The research, published in the International Journal of Medical Informatics, looked at studies from the past five years and found that AI tools are already helping doctors find cancer earlier and plan better treatments.
The study was led by Professor Saad Harous from the University of Sharjah, along with researchers from universities in Sweden, Algeria, Egypt, Saudi Arabia, and the United Arab Emirates. They reviewed 80 research papers that used AI for colon cancer diagnosis between 2020 and 2024.
These papers focused on four main areas: classification (labeling types of tissue), detection (finding tumors or polyps), segmentation (marking cancerous areas), and prediction (forecasting cancer outcomes).
One of the main uses of AI in colon cancer care is to help identify polyps during colonoscopies and to tell the difference between harmless and harmful tissue in pathology slides.
The researchers found that deep learning methods often did a better job than traditional tools in both areas. AI tools could also reduce the need for invasive procedures and help doctors spend less time reviewing images.
Professor Harous said that AI is especially useful when it can explain how it makes its decisions. This builds trust with doctors and helps them use the tools more effectively in real-life situations. He noted that “explainable AI” is more than just a nice feature—it is necessary for real medical use.
Colon cancer, also known as colorectal cancer, affects the large intestine or rectum. It is the third most common cancer in the world and one of the deadliest.
According to the World Health Organization, colon cancer caused more than 930,000 deaths in 2020 and had more than 1.9 million new cases that year. Finding ways to detect it earlier and more accurately could save many lives.
The review showed that AI models helped improve the precision of staging cancer and planning treatment. However, the researchers also pointed out some problems.
Many AI systems are tested on small or similar sets of data and don’t work as well when applied in different hospitals or with patients from different backgrounds. Also, many tools are still being tested in labs and have not yet been included in everyday hospital systems.
To fix these problems, the researchers said that AI tools need to be trained on larger, more diverse sets of data. They also need to be tested in real hospitals to prove they work for many different patients. Until that happens, the full promise of AI in cancer care will remain out of reach.
In conclusion, the study shows that AI is making real progress in helping doctors diagnose colon cancer more quickly and accurately. But to take the next step and fully use these tools in hospitals, more research and better data are needed.
With further development, AI has the potential to change the way colon cancer is detected and treated—leading to better outcomes for patients around the world.
If you care about cancer, please read studies that artificial sweeteners are linked to higher cancer risk, and how drinking milk affects risks of heart disease and cancer.
For more health information, please see recent studies about the best time to take vitamins to prevent heart disease, and results showing vitamin D supplements strongly reduces cancer death.
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