Nephrology

Performance and label efficiency of traditional deep-learning models and a retina-specific foundation model for ocular and systemic disease detection: a retrospective comparative study.

BACKGROUND: RETFound, a self-supervised retina-specific foundation model, has shown potential in downstream tasks, but its performance in comparison with that of traditional deep-learning models remains unclear. We aimed to evaluate RETFound against three supervised deep-learning models (ResNet50, ViT-Base, and SwinV2) pretrained on images from ImageNet for the detection of several ocular (disease...

Integrated multi-omics, machine learning, network toxicology, and molecular docking reveal potential mechanisms underlying methyl 4-hydroxybenzoate-associated breast cancer.

Breast cancer (BC) represents a major public-health burden, and epidemiological evidence suggests a potential association with exposure to methyl 4-hydroxybenzoate (MEP), a widely-used cosmetic preservative and estrogen-mimicking endocrine-disrupting chemical. Nevertheless, the potential mechanisms underlying MEP-associated BC oncogenesis and progression remain poorly understood. BC-related target...

Machine learning prediction models for diabetic kidney disease: A systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) has emerged as a promising tool for predicting diabetic kidney disease (DKD), yet the performance and clinical utili...

Development and Validation of an Interpretable Machine Learning Model for Predicting In-Hospital Mortality in Diabetic Patients with Sepsis-Associated Acute Kidney Injury.

BackgroundSepsis-associated acute kidney injury (SA-AKI) is a common and severe complication in critically ill patients, with poor prognosis. Diabetes...

Deep molecular profiling of lung neuroendocrine tumours and supra-carcinoids.

BACKGROUND: Lung neuroendocrine tumours (NETs, also known as carcinoids) are rapidly rising in incidence worldwide but have unknown aetiology and limi...

Recent advances and knowledge gaps in anticoagulation strategy with durable left ventricular assist devices.

Driven by technological advancements, donor shortages, and an aging population, utilization of left ventricular assist devices (LVAD), both as a bridg...

Integrating Environmental Exposure Profiles with Temporal Transcriptomics: An Explainable Machine Learning Model for Cardiovascular Disease Risk Prediction and Biological Validation.

BACKGROUND: Cardiovascular disease (CVD) pathogenesis is strongly associated with environmental exposures and metabolic factors. This study aimed to i...

Diagnostic Performance of Deep Learning Using Retinal Images for Detection of Chronic Kidney Disease: A Systematic Review and Meta-analysis.

BACKGROUND: Multiple investigations have been conducted to diagnose chronic kidney disease (CKD) from photographs of retina using deep learning models...

Multichamber Myocardial Strain for Cardiovascular Risk Stratification in Liver Transplant Recipients Using Interpretable Machine Learning.

BACKGROUND: Cardiovascular events are a leading cause of mortality after liver transplantation (LT), and existing risk scores incompletely capture myo...

Clinical phenotyping of bloodstream infections: a review of current evidence.

BACKGROUND: Bloodstream infections (BSIs) are a leading cause of morbidity and mortality, yet their clinical heterogeneity continues to challenge effe...

Integrated bulk and single-cell transcriptomic analyses identify senescence-related hub genes and microenvironmental remodeling in sarcopenia.

Increasing evidence indicates that cellular senescence, metabolic dysfunction, stromal remodeling, and immune perturbation collectively contribute to ...

Bioinformatics and Machine-Learning Identification of Pulmonary Hypertension Biomarkers and Candidate Therapeutic Compounds.

This study aimed to identify pulmonary hypertension (PH)-associated molecular biomarkers and candidate small-molecule compounds using public transcrip...

Development and internal validation of an interpretable machine learning model for predicting vancomycin-induced nephrotoxicity in hospitalized children.

INTRODUCTION: Vancomycin is widely used for severe Gram‑positive infections in children, but vancomycin‑induced nephrotoxicity (VIN) limits its safe a...

Survival Prediction for Clear Cell Renal Cell Carcinoma Based on Deep Multimodal Synergistic Survival Network.

OBJECTIVE: To propose a deep multimodal synergistic survival analysis framework (Deep Multimodal Synergistic Survival Network, DMSSN) to achieve accur...

Performance-Based Frailty Tools Capture Distinct Risk Phenotypes in Kidney Transplant Candidates: A Comparative Analysis of FRAIL and SPPB.

Frailty predicts adverse outcomes in kidney transplant candidates, but it remains unclear whether different frailty tools identify the same or distinc...

Optimizing gadolinium-enhanced CNS MRI: From physics to clinical practice.

Gadolinium-based contrast agents (GBCAs) are essential for the evaluation of central nervous system (CNS) disorders, enhancing lesion detection, chara...

HIF1A-Associated Ferroptosis-Related Gene Signatures Reveal Candidate Circulating Biomarkers in Diabetic Nephropathy.

Diabetic nephropathy (DN) is a major microvascular complication of diabetes. Hypoxia-inducible factor 1-alpha (HIF1A) and ferroptosis contribute to th...

Predictive, preventive, and personalized medicine in statin-treated patients with NSTE-ACS, HFpEF, and type 2 diabetes: a data-driven model for long-term residual risk assessment.

BACKGROUND: Despite significant advances in guideline-directed medical therapy (GDMT), statin-treated patients with non-ST-elevation acute coronary sy...

Development and validation of a multidimensional machine learning model for predicting delayed graft function in deceased donor kidney transplantation.

PURPOSE: Delayed graft function (DGF) remains a significant complication following deceased donor kidney transplantation. This study aimed to develop ...

Radiologic, Pathologic, and Deep Learning Predictors of Response to Immune Checkpoint Blockade in Renal Cell Carcinoma Patients Undergoing Post-Treatment Nephrectomy.

Response assessment of primary kidney tumors in the consolidation cytoreductive and neoadjuvant settings offers a unique opportunity to inform postope...