Given the crucial need to improve patient monitoring after surgery, the Clinical Assist AND Alert Algorithm (CASSANDRA)-Project aims at developing and evaluating the use of machine learning (ML) algorithms in detecting and predicting postoperative intra-abdominal infections and other complication entities.  The computational challenge in this field emerges from combining static preoperative risk parameters (eg. patient age, medical history, etc.) and static intraoperative data (e.g. duration, blood loss, etc.) with dynamic real time parameters on the ICU as well as on regular wards – the latter using a telemetric continuous vital parameter monitoring device. Taken together, the results may pave the way for an autonomous real-time monitoring system on surgical wards in the long term. The CASSANDRA-project will be conducted in close collaboration with the Surgical Department of the Charité - Universitätsmedizin Berlin and is funded by the Innovation Fonds of the Federal Joint Committee (Gemeinsamer Bundesausschuss G-BA) from May 2021 until April 2024.

About the project partner Charité 

The Surgical Clinic, Campus Charité Mitte|Campus Virchow Klinikum of the Charité - Universitätsmedizin Berlin is one of the largest surgical departments in Europe with over 5000 cases annually. Conducting more than 170 pancreatic, 350 liver, 500 intestinal and 170 esophageal and gastric surgical procedures per year, it is one of only a few surgical single centres providing a number of operations high enough for the development and evaluation of various machine learning algorithms. The challenging process of systematic data collection and digital storage throughout inpatient stays has already been introduced and continuously been optimized at the Campus Virchow Klinikum as part of the Enhanced Recovery After Surgery (ERAS ©)-program that works an holistic perioperative documentation concept. Our collaboratiion partners are Axel Winter, Dr. Max Maurer and Prof. Dr. Igor M. Sauer.