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Personalized prediction of mortality in patients with acute ischemic stroke using explainable artificial intelligence
12
Zitationen
12
Autoren
2024
Jahr
Abstract
Complete renal function trajectories, including AKI and AKD, are vital for fitting mortality in AIS patients. An interpretable ML model effectively clarified its decision-making process for identifying AIS patients at risk of mortality. The AI-driven web application has the potential to contribute to the development of personalized early mortality prevention.
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