Nephrology

The use of artificial intelligence to predict postoperative outcomes following percutaneous nephrolithotomy: A systematic review of prognostic modeling studies.

Artificial intelligence (AI) is increasingly applied in clinical practice to enhance prediction of postoperative outcomes. This systematic review evaluated the performance and clinical relevance of AI-based prognostic models for patients undergoing percutaneous nephrolithotomy (PCNL). A comprehensive search of PubMed, Embase, Scopus, Web of Science, and Google Scholar was conducted on 7 August 202...

Stepwise increasing input to machine learning models predicting 30-day AMI or death in emergency department chest-pain patients.

Introduction This study evaluated the performance of neural network (NN) models with stepwise increasing input for identifying acute myocardial infarction (AMI) or death within 30 days among emergency department (ED) chest-pain patients. Methods Data from 40 312 chest-pain patients were used to train NNs with increasing information in five steps. Step 1: age and sex; Step 2: past medical history, ...

Development and validation of an integrated machine learning model for recurrence-free survival prediction in clear cell renal cell carcinoma.

BACKGROUND: Integrated multimodal systems improve recurrence-free survival (RFS) prediction in surgically resected clear cell renal cell carcinoma (cc...

Identification of key biomarkers for ferroptosis in diabetic kidney disease using machine learning and WGCNA.

OBJECTIVE: Early detection of diabetic kidney disease (DKD) remains challenging because currently available clinical markers mainly reflect establishe...

RenalTox-XAI: Applicability-Domain-Constrained and Descriptor-Guided QSAR Framework for Early Screening and Safety Prioritization of Drug-Induced Renal Injury.

Drug-induced renal injury (DIRI) remains a major cause of drug attrition and post-marketing safety concerns, highlighting the need for reliable early-...

Miniaturizing and modifying natural proteins with Raygun.

Proteins have evolved over billions of years through coordinated substitutions, insertions and deletions, yet computational protein design cannot full...

Heterogeneity in the association between antihypertensive medications and Alzheimer's disease and related dementias risk: A multidimensional machine learning analysis to inform drug repurposing.

BackgroundAlzheimer's disease and related dementias (ADRD) place an immense burden on patients, families, and health systems in the United States. Hyp...

Machine learning models identify prognostic factors in systemic lupus erythematosus patients with epstein-barr virus infection.

OBJECTIVE: To identify poor prognostic factors in Epstein-Barr virus (EBV)-positive systemic lupus erythematosus (SLE) using interpretable machine-lea...

Development and external validation of a machine learning model for predicting tigecycline-associated drug-induced liver injury.

Tigecycline (TGC) is widely used to treat severe multidrug-resistant infections but can cause drug-induced liver injury. Existing prediction studies f...

Artificial intelligence predicts recurrent autoimmune hepatitis after liver transplantation in a multicenter cohort study.

BACKGROUND: Autoimmune hepatitis (AIH) is an important indication for liver transplantation (LT), but recurrence affects over 30% of recipients, threa...

Deep Neural Patchworks Predict Renal Imaging Biomarkers From Non-contrast MRI via Knowledge Transfer From Arterial-Phase Contrast-Enhanced MRI.

RATIONALE AND OBJECTIVES: Contrast-enhanced (CE) MRI provides clear corticomedullary contrast for renal compartment delineation but may be contraindic...

Strategies of Designing High-Efficiency Electrolyte Additives for Aqueous Magnesium Batteries: A Review.

With the development of next-generation energy storage systems focusing on green, safe, and sustainable devices, aqueous magnesium (Mg)-air batteries ...

Phenotypic Clustering of Idiopathic Pulmonary Arterial Hypertension: Insights Into Pulmonary Vascular and Cardiometabolic Co-Morbidity Trajectories.

Idiopathic pulmonary arterial hypertension (IPAH) exhibits significant clinical heterogeneity, necessitating a precision medicine approach. This study...

Leveraging free-text clinical records for heart disease classification through structured feature mapping.

Hypertension and diabetes are major risk factors for heart disease, which remains among the leading causes of morbidity and mortality worldwide. Heart...

Prediction and Experimental Verification of Electrolyte Solvation Structure from an OMol25-Trained Interatomic Potential.

A molecular-level understanding of electrolyte solvation structure and ion-ion correlations is critical to developing next-generation battery chemistr...

Risk Factors for Coronary Heart Disease and Stroke Among Older Adults With Metabolic Dysfunction-Associated Steatotic Liver Disease: A Nationwide Cohort Study.

BACKGROUND: Older adults with metabolic dysfunction-associated steatotic liver disease have elevated cardiovascular disease (CVD) risk, yet convention...

Optimization of Multiparametric MRI Sequence Combinations for Early Detection of Chronic Kidney Disease.

RATIONALE AND OBJECTIVES: To evaluate renal multiparametric MRI sequence combinations for early chronic kidney disease (CKD) detection and identify an...

Single-Cell and Machine Learning Analyses Identify MYDGF as an Immune-Related Biomarker Associated With the Tumor Microenvironment in Clear Cell Renal Cell Carcinoma.

Single-cell transcriptomics and machine learning methods are increasingly used to identify immune-related biomarkers in solid tumors, yet their combin...

Early hemodynamic assessment and longitudinal imaging for predicting graft outcomes post-transplant.

BACKGROUND: The early identification of early allograft dysfunction (EAD) and the long-term prediction of graft-related adverse event-free survival (G...

Highly sensitive self-powered pressure sensor with high power output based on electrochemical reactions for rehabilitation monitoring.

Self-powered electrochemical pressure sensors have aroused considerable research interest owing to their capability of sensing both static and dynamic...