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References from A machine-learning-derived online prediction model based on inflammatory and nutritional composite indicators for acute kidney injury in sepsis patients with multiple myeloma. Local targets link to admitted publications; unresolved targets remain external evidence.
Quantifying the impact of alternative definitions of sepsis-associated acute kidney injury on its incidence and outcomes: a systematic review and Meta-analysis
10.1097/ccm.0000000000006284 · 2024 · External reference
Multiple myeloma and renal failure: mechanisms, diagnosis, and management
10.7759/cureus.22585 · 2022 · External reference
Kidney disease in multiple myeloma
10.1016/j.lpm.2024.104264 · 2025 · External reference
Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review
10.1080/0886022x.2024.2380748 · 2024 · External reference
Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review
10.3389/fmed.2025.1680180 · 2025 · External reference
Prognostic nutrition index is associated with the all-cause mortality in sepsis patients: a retrospective cohort study
10.1002/jcla.24297 · 2022 · External reference
Neutrophil-to-lymphocyte ratio predicts sepsis in adult patients meeting two or more systemic inflammatory response syndrome criteria
10.5811/westjem.18466 · 2024 · External reference
Systemic immune-inflammation index (SII) as a predictor of short-term mortality risk in sepsis-associated acute kidney injury: a retrospective cohort study
10.12659/msm.943414 · 2024 · External reference
Development and validation of a predictive model for acute kidney injury in sepsis patients based on recursive partition analysis
10.1177/08850666231214243 · 2024 · External reference
The application of explainable artificial intelligence in the prediction, diagnoses, treatment, and management of chronic diseases: a systematic review
10.1177/20552076251355669 · 2025 · External reference
The third international consensus definitions for sepsis and septic shock (sepsis-3)
10.1001/jama.2016.0287 · 2016 · External reference
International myeloma working group updated criteria for the diagnosis of multiple myeloma
10.1016/s1470-2045(14)70442-5 · 2014 · External reference
Updated diagnostic criteria and staging system for multiple myeloma
10.1200/edbk_159009 · 2016 · External reference
Acute kidney injury, its definition, and treatment in adults: guidelines and reality
10.20452/pamw.15373 · 2020 · External reference
Early identification of sepsis-induced acute kidney injury by using monocyte distribution width, red-blood-cell distribution, and neutrophil-to-lymphocyte ratio
10.3390/diagnostics14090918 · 2024 · External reference
Systemic immune-inflammatory biomarkers assist in differentiating clinical features of different etiologies of acute kidney injury: results from eICU collaborative research database
10.1080/0886022x.2025.2525456 · 2025 · External reference
The role of inflammatory response and metabolic reprogramming in sepsis-associated acute kidney injury: mechanistic insights and therapeutic potential
10.3389/fimmu.2024.1487576 · 2024 · External reference
Kinetics of the lactate to albumin ratio in new onset sepsis: prognostic implications
10.3390/diagnostics14171988 · 2024 · External reference
Association between alkaline phosphatase to albumin ratio and mortality among patients with sepsis
10.1038/s41598-024-53384-7 · 2024 · External reference
Prognostic significance of albumin to alkaline phosphatase ratio in critically ill patients with acute kidney injury
10.1007/s10157-022-02234-9 · 2022 · External reference
The pathogenesis and diagnosis of acute kidney injury in multiple myeloma
10.1038/nrneph.2011.168 · 2011 · External reference
Stage prediction of acute kidney injury in sepsis patients using explainable machine learning approaches
10.3389/fmed.2025.1667488 · 2025 · External reference
ORAKLE: optimal risk prediction for mAke30 in patients with sepsis associated AKI using deep LEarning
10.1186/s13054-025-05457-w · 2025 · External reference
Personalized health monitoring using explainable AI: bridging trust in predictive healthcare
10.1038/s41598-025-15867-z · 2025 · External reference
Comparison of SHAP and clinician friendly explanations reveals effects on clinical decision behaviour
10.1038/s41746-025-01958-8 · 2025 · External reference