Nephrology

Sepsis criteria and kidney function: eliminating sex, age and economic status biases.

The kidney is a target organ for the dysregulated host response to infection that defines sepsis, an...

Comprehensive Characterization of Somatic Mutation Timing Reveals the Evolutionary Trajectory of Lung Adenocarcinoma in Chinese Patients.

UNLABELLED: Lung adenocarcinoma (LUAD) is a heterogeneous disease with substantial genomic differenc...

Discriminating Clear Cell From Non-Clear Cell Renal Cell Carcinoma: A Machine Learning Approach Using Contrast-enhanced Ultrasound Radiomics.

OBJECTIVE: The aim of this investigation is to assess the clinical usefulness of a machine learning ...

Letter to the Editor on "Deep Learning Algorithms to Predict Differential Renal Function <40% in Unilateral Hydronephrosis Based on Key Parameters of Urinary Tract Ultrasound".

Applying exposure-response analysis to enhance Mycophenolate Mofetil dosing precision in pediatric patients with immune-mediated renal diseases by machine learning models.

BACKGROUND: Mycophenolate mofetil (MMF), a cornerstone immunosuppressant for lupus nephritis, is inc...

MSFusion: A multi-source hybrid feature fusion network for accurate grading of invasive breast cancer using H&E-stained histopathological images.

Invasive breast cancer (IBC) is a prevalent malignant tumor in women, and precise grading plays a pi...

Drug repurposing to identify potential FDA-approved drugs targeting three main angiogenesis receptors through a deep learning framework.

Tumor cell survival depends on the presence of oxygen and nutrients provided by existing blood vesse...

Renal Transplant Survival Prediction From Unsupervised Deep Learning-Based Radiomics on Early Dynamic Contrast-Enhanced MRI.

RATIONALE AND OBJECTIVES: End-stage renal disease is characterized by an irreversible decline in kid...

Clinical relevance of computationally derived tubular features and their spatial relationships with the interstitial microenvironment in minimal change disease/focal segmental glomerulosclerosis.

BACKGROUND: Visual scoring of tubular damage has limitations in capturing the full spectrum of struc...

The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes.

BACKGROUND AND OBJECTIVE: Diabetes is a chronic disease characterised by a high risk of developing d...

Prediction of operation time in percutaneous nephrolithotomy (PCNL) patients: A machine learning approach.

PURPOSE: To investigate the factors influencing the length of percutaneous nephrolithotomy (PCNL) pr...

In silico design strategies for tubulin inhibitors for the development of anticancer therapies.

INTRODUCTION: Microtubules, composing of α, β-tubulin dimers, are important for cellular processes l...

Adapting to Artificial Intelligence in Nephrology Practice.

Development and Validation of Ultrasound Hemodynamic-based Prediction Models for Acute Kidney Injury After Renal Transplantation.

RATIONALE AND OBJECTIVES: Acute kidney injury (AKI) post-renal transplantation often has a poor prog...

AI-driven glomerular morphology quantification: a novel pipeline for assessing basement membrane thickness and podocyte foot process effacement in kidney diseases.

BACKGROUND AND OBJECTIVE: Measuring the thickness of the glomerular basement membrane (GBM) and asse...

Deep learning for early detection of chronic kidney disease stages in diabetes patients: A TabNet approach.

Chronic kidney disease (CKD) poses a significant risk for diabetes patients, often leading to severe...

Multiple omics-based machine learning reveals specific macrophage sub-clusters in renal ischemia-reperfusion injury and constructs predictive models for transplant outcomes.

BACKGROUND: Ischemia-reperfusion injury (IRI) is closely associated with numerous severe postoperati...

Physics-Based Inverse Modeling of Battery Degradation with Bayesian Methods.

To further improve lithium-ion batteries, a profound understanding of complex battery processes is c...

Deciphering Coulombic Efficiency of Lithium Metal Anodes by Screening Electrolyte Properties.

Coulombic efficiency (CE) is a quantifiable indicator for the reversibility of lithium metal anodes ...

Carbon-Based Catalysts for Electrosynthesis of Hydrogen Peroxide.

Hydorgen peroxide (HO) is an eco-friendly and versatile chemical with extensive applications across ...

A negative combined effect of exposure to maternal Mn-Cu-Rb-Fe metal mixtures on gestational anemia, and the mediating role of creatinine in the Guangxi Birth Cohort Study (GBCS): Twelve machine learning algorithms.

The link between individual metals and gestational anemia has been established, but the impact of me...