PREDICTING FUNCTIONAL RECOVERY AFTER STROKEA central theme in the clinical uses of AI centres around whether it can meaningfully improve prognostic assessment following acute stroke. As in the previous study, neurologists achieved an accuracy of approximately 60–65%, whereas the AI models consistently demonstrated superior performance. Developing more meaningful, objective endpoints, such as quantitative motor assessments, could enable AI models to better capture treatment effects and generate more clinically relevant predictions. Together, these findings show consideration of factors that influence clinical decisions are integral to developing sophisticated AI models. EXPANDING AI BEYOND ACUTE CAREBeyond acute stroke management, Wegener highlighted AI’s potential to strengthen secondary stroke prevention by identifying patients with previously undetected atrial fibrillation.