Nephrology

An interpretable nomogram for predicting sleep disturbance risk in maintenance hemodialysis patients.

BACKGROUND: This study aimed to develop and validate an interpretable nomogram to predict the risk o...

Mortality score in chronic coronary syndrome: prediction model from the ISCHEMIA trial.

AIMS: Accurate stratification of mortality risk is essential for management of chronic coronary synd...

Nephropathy 1 Formula (N1F) mitigates cisplatin-induced acute kidney injury by inhibiting TAK1-dependent NF-κB signaling.

ETHNOPHARMACOLOGICAL RELEVANCE: Nephropathy 1 Formula (N1F) derives from the classical traditional C...

Experimentally paired high- and low-resolution confocal fluorescence microscopy dataset for deep-learning super-resolution imaging of tooth dentin porosity.

The proposed dataset provides experimentally acquired high- and low-resolution confocal laser scanni...

Artificial Piezoelectric Interface Enables Ultrafast Interfacial Ion Kinetic for Highly-Sensitive Piezoionic Sensors.

Flexible piezoionic sensors are promising in artificial intelligence and biomedical engineering, whi...

Risk prediction modelling of 30-day all-cause mortality following percutaneous coronary intervention in an Australian population: leveraging machine learning.

BACKGROUND: Preprocedural risk prediction of 30-day all-cause mortality after percutaneous coronary ...

MedFusion-gP-AKI: development and multicenter validation of a machine learning fusion model for early prediction of KDIGO stage 3 acute kidney injury in critically ill traumatic cervicothoracic spinal cord injury patients.

KDIGO stage-3 acute kidney injury (AKI), a life-threatening complication in critically ill patients ...

A nine-gene diagnostic model for IgA nephropathy based on multi-cohort machine learning: integrating gene expression and immunohistochemical validation.

IgA nephropathy (IgAN) is the most common primary glomerulonephritis, requiring improved diagnostic ...

Integrating pesticide molecular, soil, and electrolyte features through tree-based ensemble learning for accurate sorption prediction.

Although machine learning (ML) has been increasingly used to predict pesticide sorption, most existi...

Multiphase CT-based deep learning radiomics nomogram models for preoperative WHO/ISUP grading of clear cell renal cell carcinoma: a two-center validation study.

BACKGROUND: Preoperative determination of clear cell renal cell carcinoma (ccRCC) World Health Organ...

Machine learning-based prognostic analysis of patients with status epilepticus in the neurological intensive care unit.

OBJECTIVE: This study aimed to develop and validate machine learning (ML) models for predicting the ...

Predicting Electrolyte Stability in Lithium and Post-Lithium Metal Batteries: The Failure of Linear Single Descriptor-Based Models.

A stable solid electrolyte interphase (SEI), formed by the reductive decomposition of electrolytes a...

Unveiling Endotypes in Systemic Lupus Erythematosus Through Multi-Omic Analysis: Insights into Cardiovascular and Renal Complications.

BACKGROUND: Systemic lupus erythematosus (SLE) shows clinical and molecular heterogeneity, and cardi...

Applications of artificial intelligence algorithms in ultrasound-based kidney stone detection, classification, prediction, and management: a systematic review.

BACKGROUND: Kidney stones are a prevalent urological condition with significant global burden, often...

DNA-Logic Trimodal Biofuel Cell Platform for AI-Assisted Dual Pathogen Detection.

A DNA-logic-gated, trimodal, self-powered biosensing platform is developed for the rapid, simultaneo...

Comparison and Interpretation of Ultrasound-Based Radiomics Machine Learning Models for Assessing Renal Fibrosis in Chronic Kidney Disease.

Renal fibrosis is a key pathological feature of chronic kidney disease (CKD), yet its noninvasive ev...

Promoting clinical trials in pediatric IgA nephropathy through extrapolation: an artificial intelligence-enhanced literature review of the disease in pediatrics sponsored by the Kidney Health Initiative.

BACKGROUND: There is an urgent need to evaluate the efficacy of novel therapeutics that have been ap...

Deep learning approaches for time series prediction of renal recovery in medical critically Ill patients with acute kidney injury: LSTM, GRU, and transformer models.

Cation dominated but negatively charged Na2SO4,aq-graphene interfaces.

The distribution of ions and their impact on the structure of electrolyte interfaces plays an import...

Preoperative Risk Score for Mortality Within 3 Years of Elective Aortobifemoral Artery Bypass.

BACKGROUND: The purpose of this study was to create a risk score for mortality within 3 years of ele...

Role of the gut microbiome in shaping drug response in immunocompromised hosts.

BACKGROUND: There is an increasing amount of evidence on microbiome-drug interactions in several cli...