
AI solution for use in cancer surgery
Complications following bowel cancer surgery are common and can lead to lasting impairments and, in the worst cases, even death. This project investigates how an AI tool can be used to improve treatment outcomes.


Innovative research in this project will create important improvements in cancer surgery.
Researchers will delve into the Norwegian cancer registry, which has the potential to improve patient care. Currently, one in four bowel cancer patients experiences complications after surgery, leading to readmissions, permanent damage, or even death. Additionally, one in four suffers a cancer recurrence within three years, often resulting in long-term impacts that affect their ability to work. These complications bring high personal and societal costs. Therefore, Zealand University Hospital in Køge and the Oslo University Hospital Cancer Registry will leverage big data and AI. SUH’s Department of Surgery has developed a prototype for an algorithm-based tool that uses large amounts of patient data to to support clinical decisions for bowel cancer care. However, to enhance and clinically validate this tool, more data is essential.
Norwegian Cancer Registry to be utilized
In this bridge-building project, the goal is to establish and strengthen the network with the Norwegian Cancer Registry and assess how Norwegian patient data can enhance the algorithms, making the AI tool implementable in Norwegian hospitals. The project will foster knowledge-sharing across teams, conduct initial analyses, and facilitate introductory meetings with relevant companies and potential partners. This bridge-building effort lays the foundation for a future main project with the potential to revolutionize bowel cancer treatment.
The AI tool, tailored for bowel cancer treatment, will be further developed using extensive patient data specific to this cancer type in the program region. In its completed form, the tool will support healthcare professionals in customizing treatments to optimize individual patient outcomes. Currently, doctors base their treatment choices on experience, patient discussions, and medical records, often considering around seven to ten data points. In contrast, an AI-based tool can analyze 200,000 data points—covering genetics, similar patient histories, and more—to produce its recommendations. The tool will predict the most effective treatment for each patient and identify supportive measures, like preoperative training, that may improve recovery.




Project Partners
- Surgical Department, Center for Surgical Science, Zealand University Hospital
- Kreftregisteret, Oslo University Hospital
- The Research Department, Zealand University Hospital
This bridge-building project is partly financed by Interreg Öresund-Kattegat-Skagerrak.
The results from this bridge-building project is being utilized in the project FLORENCE.