Nephrology

Exploring predictive models for intradialytic hypotension risk in maintenance hemodialysis patients: A systematic review.

BACKGROUND: This systematic review evaluates existing risk prediction models for intradialytic hypotension (IDH) in maintenance hemodialysis (MHD) patients, aiming to inform the development of high-quality predictive tools for clinical use.

Label-Free Evaluation of Lung and Heart Transplant Biopsies Using Tissue Autofluorescence-Based Virtual Staining.

We present a panel of virtual staining neural networks for lung and heart transplant biopsies, providing rapid and high-quality histological staining results while bypassing the traditional histochemical staining process. Allograft rejection is a common complication of organ transplantation, which can lead to life-threatening outcomes if not promptly managed. Histological examination is the gold...

A Multimodal Predictive Model for Chronic Kidney Disease and Its Association With Vascular Complications in Patients With Type 2 Diabetes: Model Development and Validation Study in South Korea and the U.K.

OBJECTIVE: To develop a multimodal model to predict chronic kidney disease (CKD) in patients with type 2 diabetes mellitus (T2DM), given the limited r...

A manganese metabolism-related gene signature stratifies prognosis and immunotherapy efficacy in kidney cancer.

BACKGROUND: Manganese modulates tumorigenesis and immune regulation. High levels of manganese may promote cancer progression. While manganese toxicity...

The Role of Precision Nutrition in Kidney Disease.

Precision nutrition utilizes an individualized approach in which dietary interventions are tailored according to patients' genetic, biologic, and envi...

Predicting long-term kidney graft failure using novel multi-omic blood-based biomarkers and artificial intelligence tools.

Kidney transplantation (KT) remains the preferred treatment for end-stage renal disease. With advancements in immunosuppressive regimens and KT survei...

Deep learning model for grading carcinoma with Gini-based feature selection and linear production-inspired feature fusion.

The most common types of kidneys and liver cancer are renal cell carcinoma (RCC) and hepatic cell carcinoma (HCC), respectively. Accurate grading of t...

A textual dataset of de-identified health records in Spanish and Catalan for medical entity recognition and anonymization.

The advancement of clinical natural language processing systems is crucial to exploit the wealth of textual data contained in medical records. Diverse...

A supervised machine learning approach with feature selection for sex-specific biomarker prediction.

Biomarkers are crucial in aiding in disease diagnosis, prognosis, and treatment selection. Machine learning (ML) has emerged as an effective tool for ...

GenAI exceeds clinical experts in predicting acute kidney injury following paediatric cardiopulmonary bypass.

The emergence of large language models (LLMs) opens new horizons to leverage, often unused, information in clinical text. Our study aims to capitalise...

Personalized prediction model generated with machine learning for kidney function one year after living kidney donation.

Living kidney donors typically experience approximately a 30% reduction in kidney function after donation, although the degree of reduction varies amo...

Identification of aging-related biomarkers and immune infiltration analysis in renal stones by integrated bioinformatics analysis.

Renal stones (RS) are common urologic condition with unclear pathogenesis. Role of aging-related differentially expressed genes (ARDEGs) in RS remains...

Deep-learning-based automated prediction of mouse seminiferous tubule stage by using bright-field microscopy.

Infertility is a global issue, and approximately 50% of cases are due to male factors, with defective spermatogenesis being the main one. For studies ...

Identification of CXCR4 as a potential preventive gene in clear cell renal cell carcinoma from machine learning and immune analysis.

Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignant kidney tumor characterized by high metastatic potential and recurrence rates....

Identification of potential pathogenic genes associated with the comorbidity of rheumatoid arthritis and renal fibrosis using bioinformatics and machine learning.

This study aimed to identify the potential pathogenic genes associated with the comorbidity of rheumatoid arthritis (RA) and renal fibrosis (RF). Tran...

Computed tomography-based radiomics predicts prognostic and treatment-related levels of immune infiltration in the immune microenvironment of clear cell renal cell carcinoma.

OBJECTIVES: The composition of the tumour microenvironment is very complex, and measuring the extent of immune cell infiltration can provide an import...

Machine learning-based prediction model for arteriovenous fistula thrombosis risk: a retrospective cohort study from 2017 to 2024.

BACKGROUND: Thrombosis of arteriovenous fistulas represents a prevalent complication among patients undergoing hemodialysis, characterized by a notabl...

An explainable machine learning model for early warning of hypertensive and hypotensive anomalies in maintenance hemodialysis patients.

BACKGROUND: Intradialytic hypotension (IDH) and intradialytic hypertension (IDHTN) are major complications of maintenance hemodialysis (MHD) that sign...

Transforming heart transplantation care with multi-omics insights.

Heart transplantation (HTx) remains the definitive treatment for patients with end-stage heart disease. Despite the number of HTx performed annually i...

Method for Predict Stenosis of Arteriovenous Fistula Patients Based on Machine Learning.

OBJECTIVES: Arteriovenous fistula (AVF) is the most ideal vascular access for hemodialysis. People with AVF have a longer vascular access survival rat...