Partner contact: Ismail Labgaa
EPFL laboratory: Machine Learning and Optimization Laboratory (MLO), intelligent Global Health Research group
EPFL contact: Mary-Anne Hartley
Major digestive surgery is associated with a high comorbidity (i.e. high risk of complications after surgery). Postoperative complications (POC) are adverse events that deleteriously impact patients outcomes. Anticipating POC or at least identifying patients at high risk to develop POC may help and guide clinicians in the postoperative management of surgical patients. Unfortunately, the available tools in clinical practice are of restraint value due to their limited accuracy. There is a critical unmet need to identify new predictors of POC in surgery.
Recently, artificial intelligence (AI) has shown a meteoric rise in medicine, showing numerous clinical applications but its role to predict POC remains unknown.
Herein, we aim to use AI to develop new models allowing to improve the prediction of POC in a dataset of >2000 patients undergoing major digestive surgery.