Project Details


The aim is to investigate whether AI can identify patients at high risk of mortality following colorectal surgery. To achieve that, the project will collaborate with other colorectal groups to pool the data and produce a dataset of routinely collected clinical and administrative data held. Statistical analysis will then be conducted to find any significant variables.

Colorectal cancer is the third most common cancer by incidence, with over 1.8 million new cases in 2018, and the second most common cause of cancer death when the sexes are combined [1]. The economic impact of colorectal cancer on healthcare systems is intense. In the UK, the cost of diagnosing and treating colorectal cancer patients is significant (€40,000 per case) and exacerbates funding constraints on the National Health Service (NHS). With limited resources and a finite surgical bed capacity in many hospitals, it is important to know the mortality rate(s) after elective CRC surgery.

Mortality is an essential proxy of quality of care in surgery. Overall mortality rates following colorectal surgery range from 1 to 16.4%.

An accurate prediction of mortality would help healthcare professionals with planning, decision making and building strategies. This will eventually lead to improved patient care and prevent some mortality . A prediction model could be valuable to surgeons and healthcare institutions. An accurate mortality prediction model would contribute to patient risk stratification, preoperative consultation with the patient and family members, decision-making process, consent and professional accountability.
Short titleAI for rectal cancer
Effective start/end date1/06/2228/02/25