In the program, we address two proof-of-concept applications to develop AI technology to support real clinical decision-making, perform validation, and initiate valorization.
In the first application, we will develop AI-driven decision-making for coagulation and transfusion strategies serving hospitalized patients that undergo major surgery and have a high risk of bleeding. In the second application, we will design AI-driven decision-making to identify the risk of hospitalization in non-hospitalized cardiac patients with heart failure using a multi-modal data analysis. When health decision-making is supported by machines and data, it affects the autonomy of health professionals and their patients. We will investigate how this legal-ethical relationship is affected by the introduction of AI-supported decision-making in healthcare, and integrate ethical and legal research at every stage of its development.
In this meeting, we program consortium will meet to discuss first steps and future directions.
Welcome and introduction to the program
Decision-making for coagulation and transfusion strategies
Decision-making for determining the risk of hospitalization in heart failure;
Data Bodies – AI Competitions as Infrastructures: Examining Power Relations on Kaggle and Grand Challenge in AI-Driven Medical Imaging
AI in Healthcare: The Impact on Professional Autonomy and Good Practice
Alexander Vlaar/Ivana Išgum