KIPeriOP: Entwicklung von KI-basierter klinischer Entscheidungsunterstützung im perioperativen Risikomanagement.
© Fraunhofer MEVIS
Illustration of clinical decision support for different treatment options

KIPeriOP is a research project funded by the German Federal Ministry of Health (BMG) with the aim of improving perioperative risk management and reducing perioperative mortality and permanent damage. Clinical guidelines already support perioperative decision-making and will be complemented in the project by the trustworthy use of artificial intelligence, including the prediction of postoperative risks based on preoperative risk factors. The project consortium combines outstanding clinical, technical, ethical and economic expertise and is led by the University Hospital of Würzburg (clinical coordination) and the Fraunhofer Institute for Digital Medicine MEVIS (technical coordination).




  • Data for Health Conference 2023, Federal Ministry of Health – Berlin, June 20-21, 2023
  • Rieke Alpers, Sebastian Daniel Boie, Eduardo Salgado, Felix Balzer, Markus Hüllebrand, Anja Hennemuth, Pamela Bendz, Sophia Schmee, Max Westphal. Efficiently involving clinical experts for handling missing data: a case study. Accepted for the  5th Conference of the Central European Network: From Data to Knowledge. Advancing Life Sciences, Basel, 3.-7. September, 2023: From Data to Knowledge. Advancing Life Sciences. (cen2023.github.io)
  • Rieke Alpers, Sebastian Daniel Boie, Eduardo Salgado, Felix Balzer, Anja Hennemuth, Markus Hüllebrand, Max Westphal. ML-based predictive modelling on routine data for preoperative risk assessment: investigation of common pitfalls and solutions. Accepted for 68. GMDS-Jahrestagung, Heilbronn, 17.-21. September 2023: GMDS 2023 - 68. GMDS-Jahrestagung | HHN