To improve adequate blood product therapy viscoelastic hemostatic assay (VHA), has been introduced. This assay not only replaces separate and more laborious testing but saves significant time between blood draw and results. However, VHA derived parameters are difficult to interpret, which limits the application. Therefore this project aims to develop AI-driven decision-making for coagulation and transfusion strategies serving hospitalized patients that undergo major surgery and have a high risk of bleeding. We aim to create a model that is able to interpret the collected VHA parameters and, in combination with other clinical parameters, able to guide the anesthesiologist and intensivist in the choice and amount of coagulation agent. At the same time, we will explore the professional medical standard and professional autonomy that is involved in the health decision-making in this specific case, before the implementation of health AI decision-making. This project is part of the UvA Research Priority Agenda AI for Health Decision-Making, which is a collaboration between Faculties of Medicine, Science, Humanities and Law.