Artificial Intelligence-Based Prediction of Complications in Intensive Care Units
Spin-Off
Project WebsiteIntensive care units (ICU) are highly challenging environments that present clinical teams with a demanding caseload, data or input overload, and require rapid decision making, often in reactive behavior once problems become apparent. Post-operative complications can significantly increase mortality for 100.000 patients per year in Germany, and can result in recurrent surgeries, and longer stays at the intensive care unit, which causes a substantial economic burden for hospitals.
Alexander Meyer
(DHZC)
Project Lead
To solve this challenge, the team x-cardiac developed a real-time AI-based platform solution to recognize postoperative complications, e.g., severe internal bleeding, enabling ICU staff in real-time to intervene before the devastating consequences manifest. The team’s vision is to break the “deadly triad of cardiac surgery” to improve patient care, reduce mortality, and reduce the length of stay at intensive care units (ICU), thereby improving health system economics, and enable healthcare professionals.
The team consists of a cardiac surgeon/computer scientist, experienced machine learning experts, and software developers. The resulting company, X-cardiac, spun off in 2021 and is based in Berlin. Their internal bleeding module is clinically validated in a study with 10.000 patients, published in The Lancet Respiratory Medicine, and is CE certified. The team is currently developing its second module to predict renal failure.
