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Figure 1. Artificial intelligence in cardiac surgery-associated acute kidney injury management: a comprehensive framework. Figure 1 illustrates the multidimensional framework of AI applications in CSA-AKI management. The framework is organized into six core layers: (1) multimodal data integration, encompassing preoperative, intraoperative, and postoperative data sources; (2) AI-driven core applications, including early prediction, subtype classification, and prognostic assessment, with representative studies and performance metrics; (3) clinical utility, highlighting key outcomes such as early warning, personalized treatment, and cardio-renal composite endpoints; (4) key challenges and considerations for clinical translation, including data quality, model interpretability, and implementation costs; (5) evidence-supported applications; and (6) future research directions. AI: Artificial intelligence; CSA-AKI: cardiac surgery-associated acute kidney injury; CVP: central venous pressure; MAP: mean arterial pressure; TPP: tissue perfusion pressure; CPB: cardiopulmonary bypass; CKD: chronic kidney disease; TRIPOD: Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis; PROBAST: Prediction model Risk Of Bias ASsessment Tool; SHAP: SHapley Additive exPlanations; LIME: local interpretable model-agnostic explanations.