Personalizing renal replacement therapy initiation in the intensive care unit: a reinforcement learning-based strategy with external validation on the AKIKI randomized controlled trials.
The timely initiation of renal replacement therapy (RRT) for acute kidney injury (AKI) requires sequential decision-making tailored to individuals' evolving characteristics. To learn and validate optimal strategies for RRT initiation, we used reinforcement learning on clinical data from routine care and randomized controlled trials.
Author(s): Grolleau, François, Petit, François, Gaudry, Stéphane, Diard, Élise, Quenot, Jean-Pierre, Dreyfuss, Didier, Tran, Viet-Thi, Porcher, Raphaël
DOI: 10.1093/jamia/ocae004