Nephrology

Streamlining the Histopathologic Workflow in Diabetic Kidney Disease with Artificial Intelligence.

KEY POINTS: Artificial intelligence models effectively generalized across studies and animal models and reduced translational gaps when applied to human biopsies. Artificial intelligence assistance reduced study evaluation turnaround times by up to 90% versus manual whole slide imaging scoring, matching expert-level performance. Self-supervised learning captured diabetic kidney disease-relevant fe...

Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.

Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalence rising due to aging populations, diabetes, hypertension, and environmental factors. Conventional risk assessment tools such as the CKD Epidemiology Collaboration equation and the Kidney Failure Risk Equation are limited in precision, generalizability, and their ability to identify rapid progresso...

Predictive value of dynamic creatinine cumulative exposure and trajectory classification onmortality in severe acute pancreatitis: a multicenter retrospective cohort study.

AIMS: This study aims to evaluate the predictive value of cumulative creatinine exposure (CumCr) and dynamic creatinine trajectories for severe acute ...

AI-powered chronic kidney disease detection integrating TabNet and LSTM for precision diagnosis.

Chronic kidney disease (CKD) is a leading cause of morbidity and mortality worldwide, with early detection being vital for effective treatment and man...

Responsible Use of Artificial Intelligence to Improve Kidney Care: A Statement from the American Society of Nephrology.

Artificial intelligence (AI) is rapidly transforming the delivery of kidney care through predictive analytics, machine learning, deep learning, and ge...

The application of machine learning in the evaluation of urinary tract infections incidence in patients in a Nursing and Treatment Facility.

BACKGROUND: Urinary tract infection (UTI) is a serious problem in the healthcare system. It is caused by bacteria from the gastrointestinal tract. The...

Renal Cell Carcinoma subtyping: Learning from multi-resolution localization.

BACKGROUND AND OBJECTIVE: Renal Cell Carcinoma (RCC) is often diagnosed at advanced stages, limiting treatment options. Since prognosis depends on tum...

Machine Learning-Based Analysis of UF-5000 Scattergrams Improves the Identification of Urinary Dysmorphic Red Blood Cells.

BACKGROUND: Identifying dysmorphic red blood cells (RBCs) is critical for diagnosing glomerular diseases, as distinguishing glomerular from non-glomer...

Construction and validation of a hypertensive nephropathy diagnostic model based on mitochondrial-related genes using machine learning combined with WGCNA.

BACKGROUND: Hypertensive nephropathy (HTN) arises from chronic hypertension and may potentially result in severe renal failure. Due to the absence of ...

Automatically Measuring Kidney, Liver, and Cyst Volumes in Autosomal Dominant Polycystic Kidney Disease.

KEY POINTS: TraceOrg is a web-based tool that automatically labels kidney, liver, and cysts, reporting volumes and Mayo Imaging Classification. Extern...

Artificial intelligence-based segmentation of small renal masses: a multi-center, multi-scanner, multi-sequence study.

OBJECTIVES: This study aims to develop an artificial intelligence (AI)-based automated segmentation method for small renal masses (SRMs) using multi-c...

Comparison of glass-based and whole-slide image-based grade assignment for clear-cell and papillary renal cell carcinoma: a multi-cohort, international reproducibility study.

BACKGROUND AND AIMS: Histological grading of renal cell carcinoma (RCC) is an important part of diagnostic evaluation. Reproducibility of RCC grading ...

An Interpretable Machine Learning Model for Early Multitemporal Prediction of Onset of Acute Kidney Injury in Intensive Care Unit Patients with Severe Trauma.

Background: Acute Kidney Injury (AKI), a leading organ failure cause in critical patients, demands early high-risk identification to enhance outcomes....

Correction to: Kidney Week 2025 Abstract Artificial Intelligence in Autosomal Dominant Polycystic Kidney Disease: Transforming Diagnosis, Risk Stratification, and Therapeutic Interventions SA-PO0555.

Using precision medicine methods to identify disease stages for chronic limb-threatening ischemia in participants of the BEST-CLI trial.

BACKGROUND: Chronic limb-threatening ischemia (CLTI), the most severe form of peripheral artery disease, is associated with a high risk of limb loss. ...

A brief review of some artificial intelligence methods in nephrology.

This brief, focused review considers two of the more commonly used artificial intelligence (AI) methods encountered in nephrology publications: machin...

Perioperative Extracorporeal Membrane Oxygenation Use in Lung Transplantation: Analysis of Outcomes and Future Directions.

Extracorporeal membrane oxygenation (ECMO) has emerged as a critical intervention in the management of patients with end-stage lung disease undergoing...

"PD-PREDICT": A Machine Learning Model for Patient Survival in Peritoneal Dialysis.

Accurate survival prediction in peritoneal dialysis (PD) patients is essential for personalized treatment planning and shared decision-making. We deve...

Early prediction of septic shock in ICU patients using machine learning: development, external validation, and explainability with SHAP.

BACKGROUND: Septic shock is a severe and life-threatening complication of sepsis associated with high mortality. Early identification remains challeng...

Association between triglyceride-glucose index and depression and the mediating role of hypertension: a cross-sectional study of obese adults.

BACKGROUND: Recent findings indicate a positive correlation between the TyG (triglyceride-glucose) index and the incidence of depression. However, the...