Nephrology

Randomized trial of electronic health record implemented AI risk prediction in kidney transplant care.

Artificial intelligence (AI)-based risk prediction is increasingly implemented in clinical care, but randomized evidence on communication and shared decision-making (SDM) outcomes is limited. In the single-center PRIMA-AI trial, 76 kidney transplant recipients with estimated glomerular filtration rate <30 mL/min/1.73 m² were randomized 1:1 to usual care or usual care plus an electronic health reco...

Short-Range Machine-Learning Potentials for Aqueous Electrolyte Solutions.

Machine-learning potentials (MLPs) extend the time and length scales of atomistic simulations, enabling the study of complex systems, such as electrolyte solutions. Yet most models face a tradeoff between accuracy, computational cost, and the ability to capture long-range interactions. Large foundation models promise generality but often come with substantial overhead and energy demands. In contra...

Forging Sustainable Carbon-Nitrogen Bonds from CO2 and NOx: Mechanistic Insights and Catalyst Design for Electrochemical CN Coupling.

Electrochemical CN coupling between carbon sources (CO2, CO) and nitrogen feedstocks (NOx) offers a sustainable route to synthesize value-added organ...

Glo-MMF: A modular multi-model framework for automated morphometry of glomerular ultrastructural features.

BACKGROUND AND OBJECTIVE: Automated morphological analysis of glomerular ultrastructures facilitates diagnosis by reducing pathologists' burden and im...

Blood biomarker trajectories in ICU-directed prediction models - A scoping review.

BACKGROUND: Despite advanced analytical methods and increasing data availability, most intensive care unit (ICU) prediction models rely on static meas...

Predicting anemia treatment outcomes in maintenance hemodialysis patients using multiple machine learning models.

BACKGROUND: Based on machine learning prediction models, we explored the anemia treatment attainment of patients on maintenance hemodialysis (MHD) and...

Deep-learning time-series anomaly detection of acute kidney injury from creatinine-eGFR trajectories in the ICU.

Acute kidney injury (AKI) is common in the intensive care unit (ICU), and fixed creatinine thresholds may miss clinically relevant dynamics. We tested...

Integrative bioinformatic analysis prioritizes TIMP1 and FN1 as angiogenesis-related candidate genes in diabetic foot ulcers.

BACKGROUND: Diabetic foot ulcers (DFUs) represent a severe chronic complication of diabetes and are characterized by persistent impairment of wound he...

Machine learning to predict survival in patients treated for hepatocellular carcinoma: a systematic review.

BACKGROUND: Given the interplay of cirrhosis with malignancy, management of hepatocellular carcinoma (HCC) relies on multidisciplinary clinician judge...

Machine learning model predicts acute kidney injury in pediatric patients after cardiac surgery: a systematic review and meta-analysis.

BACKGROUND: Acute kidney injury (AKI) is a common complication following pediatric cardiac surgery, frequently leading to poor outcomes and even death...

Development and external validation of an interpretable early prediction model for acute kidney injury using TabPFN and routine admission data: a retrospective cohort study.

BACKGROUND: Acute kidney injury (AKI) is a common and serious complication among hospitalized patients, and early risk stratification remains challeng...

Blood Pressure Assessment Across the Lifespan: Improving Clinical Research and Clinical Practice: A National Heart, Lung, and Blood Institute Workshop Report.

Hypertension is a modifiable risk factor for cardiovascular disease (CVD) and its prevalence is high in the United States and worldwide. Adequate char...

Serum KIM-1 molecular early warning radar: SERS combined with artificial intelligence for accurate early diagnosis of chronic kidney disease.

Chronic kidney disease (CKD) has become a major global public health issue. Due to its insidious onset and atypical early symptoms, patients often fai...

Design and validation of renal stone detection using multi-architecture feature extraction with deep sequential learning model on axial computed tomography images.

Kidney stone disease is a significant public health threat, with its prevalence escalating due to evolving dietary habits, rising rates of obesity, ot...

Multimodal predictions of end stage chronic kidney disease from asymptomatic individuals for discovery of genomic biomarkers.

Chronic kidney disease (CKD) is a complex condition where the kidneys are damaged and progressively lose their ability to filter blood, 10% of the wor...

Associations of Red Blood Cell Distribution Width-Derived Indicators and Their Longitudinal Dynamic Trajectories With Mortality Risk in Critically Ill Patients With Pulmonary Hypertension.

Red blood cell distribution width (RDW)-derived indicators have increasingly been recognized as biomarkers reflecting systemic inflammation and hemato...

Development and internal validation of an explainable machine-learning model to predict 3-year overall survival rate after radical cystectomy.

BACKGROUND: This study aimed to develop and internally validate an explainable machine-learning model using routinely available clinicopathologic and ...

A TyG-UHR-based machine learning model for screening lean MAFLD: development and external validation.

BACKGROUND: Lean metabolic dysfunction-associated fatty liver disease (MAFLD) is increasingly recognized but often goes unnoticed during health checku...

Cardiovascular Risk Stratification in Youth-Onset Type 2 Diabetes Using Machine Learning.

BACKGROUND: The rising incidence of youth-onset type 2 diabetes mellitus (T2DM), along with the risk of early cardiovascular complications, is concern...

Tubulointerstitial Diseases: An Updated Framework for Diverse and Emerging Entities.

Tubulointerstitial diseases represent a heterogeneous group of kidney diseases with diverse causes and overlapping histopathologic and immunophenotypi...