Development of Machine Learning Models for the Prediction of Complications After Colonic, Colorectal and Small Intestine Anastomosis in Psy…
The study aims to create a predictive modeling service for postoperative complications and prolonged hospital stay in patients with psychiatric diseases undergoing colorectal surgery. It also investigates how preoperative risk factors, psychiatric and psychosomatic diseases affect colorectal surgery outcomes and complications such as anastomosis insufficiency using predictive modeling techniques. The resulting service will be publicly available as a web-based application.
The study aims to create a predictive modeling service for postoperative complications and prolonged hospital stay in patients with psychiatric diseases undergoing colorectal surgery. It also investigates how preoperative risk factors, psychiatric and psychosomatic diseases affect colorectal surgery outcomes and complications such as anastomosis insufficiency using predictive modeling techniques. The resulting service will be publicly available as a web-based application.
The development of a publicly accessible AI-driven predictive tool aligns with Swiss AI initiatives to improve healthcare outcomes through data-driven decision support.
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