Predicting essential proxies for quality of surgical care

The research is investigating the use of AI, data analytics, and machine learning algorithms to identify significant predictor variables to identify patients at high risk of a long stay, readmission, and/or mortality following surgery. Moreover, the research looks for innovative knowledge-based AI to convert findings into actionable recommendations.

To achieve that, the team are attempting to collaborate with other colorectal groups to pool data and then to produce a richer dataset of clinical and administrative data.

Once that is achieved, the group plans to perform statistical and data analysis to find the significant variables that might help create new prediction models.

Explainable AI-derived early risk prediction models for length of stay, readmission and mortality will be created.