Print Email Facebook Twitter The future of artificial intelligence in intensive care Title The future of artificial intelligence in intensive care: moving from predictive to actionable AI Author Smit, J.M. (TU Delft Pattern Recognition and Bioinformatics; Erasmus MC) Krijthe, J.H. (TU Delft Pattern Recognition and Bioinformatics) van Bommel, Jasper (Erasmus MC) van Genderen, M. E. Labrecque, J. A. Komorowski, M. Gommers, D.A.M.P.J. (TU Delft Biomechanical Engineering) Reinders, M.J.T. (TU Delft Pattern Recognition and Bioinformatics) Department Biomechanical Engineering Date 2023 Abstract Artificial intelligence (AI) research in the intensive care unit (ICU) mainly focuses on developing models (from linear regression to deep learning) to predict out-comes, such as mortality or sepsis [1, 2]. However, there is another important aspect of AI that is typically not framed as AI (although it may be more worthy of the name), which is the prediction of patient outcomes or events that would result from different actions, known as causal inference [3, 4]. This aspect of AI is crucial for decision-making in the ICU. To emphasize the impor- tance of causal inference, we propose to refer to any data- driven model used for causal inference tasks as ‘action- able AI’, as opposed to ‘predictive AI’, and discuss how these models could provide meaningful decision support in the ICU. To reference this document use: http://resolver.tudelft.nl/uuid:38dd500a-7e71-4ae1-9b38-3d8c756c2637 DOI https://doi.org/10.1007/s00134-023-07102-y ISSN 0342-4642 Source Intensive Care Medicine, 49 (9), 1114-1116 Part of collection Institutional Repository Document type journal article Rights © 2023 , J.M. Smit, J.H. Krijthe, Jasper van Bommel, M. E. van Genderen, J. A. Labrecque, M. Komorowski, D.A.M.P.J. Gommers, M.J.T. Reinders Files PDF s00134_023_07102_y.pdf 1.33 MB Close viewer /islandora/object/uuid:38dd500a-7e71-4ae1-9b38-3d8c756c2637/datastream/OBJ/view