Nephrology

Gene as a Molecular Target Potentially Shared by Idiopathic Pulmonary Fibrosis and Pulmonary Hypertension: Drug Repurposing Prospect with Aminoglutethimide.

Idiopathic pulmonary fibrosis (IPF) and pulmonary hypertension (PH) are two chronic conditions that can coexist occasionally, resulting in high morbidity and mortality. Despite their clinical association, the underlying genetic mechanisms and therapeutic targets that might link these two chronic disorders remain poorly understood. The present study used analyses and machine learning to uncover ge...

Identification of lipid metabolism-associated biomarkers in lupus nephritis by SVM model and therapeutic potential of Alisol B 23-acetate.

Systemic lupus erythematosus (SLE), a multifaceted autoimmune disorder, has lupus nephritis (LN) as one of its grave complications and is strongly associated with dyslipidemia. This investigation sought to delineate renal-specific lipid metabolism-related genes (LMRGs) signatures in lupus nephritis (LN) through integrated bioinformatics analysis and explore the therapeutic effect of Alisol B 23-ac...

Statistical consideration in nephrology research.

Nephrology research plays an important role in advancing our understanding of kidney disease and improving patient outcomes. However, the complexity o...

Building Trust in Clinical AI: A Web-Based Explainable Decision Support System for Chronic Kidney Disease.

Chronic Kidney Disease (CKD) is a significant global public health issue, affecting over 10% of the population. Timely diagnosis is crucial for effect...

Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques.

The rapid decline of kidney function in middle-aged and elderly people has become an increasingly serious public health problem. Machine learning (ML)...

Transferability of Data Sets between Machine-Learned Interatomic Potential Algorithms.

The emergence of Foundational Machine Learning Interatomic Potential (FMLIP) models trained on extensive data sets motivates attempts to transfer data...

Improving Covalent and Noncovalent Molecule Generation via Reinforcement Learning with Functional Fragments.

Small-molecule drugs play a critical role in cancer therapy by selectively targeting key signaling pathways that drive tumor growth. While deep learni...

Case-control study combined with machine learning techniques to identify key genetic variations in GSK3B that affect susceptibility to diabetic kidney diseases.

The role of genetic susceptibility in early warning and precise treatment of diabetic kidney disease (DKD) requires further investigation. A case-cont...

Machine learning-based prediction model for cognitive impairment risk in patients with chronic kidney disease.

BACKGROUND: The high prevalence of cognitive impairment (CI) in Chronic kidney disease (CKD) patients impacts their quality of life and prognosis, yet...

Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis-induced myocardial injury (SIMI). Prompt and earl...

Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China.

BACKGROUND: Cardiovascular-Kidney-Metabolic (CKM) syndrome is a systemic disease characterized by pathophysiological interactions between the cardiova...

Evaluation of early donor renal function recovery after living-donor nephrectomy as a predictor of allograft failure after kidney transplantation: a longitudinal cohort and machine learning study.

BACKGROUND: Kidney transplant recipients continue to face a significant long-term risk of death-censored allograft failure (DCGF). We aimed to evaluat...

A machine learning-based prediction model for sepsis-associated delirium in intensive care unit patients with sepsis-associated acute kidney injury.

Sepsis-associated acute kidney injury (SA-AKI) patients in the ICU often suffer from sepsis-associated delirium (SAD), which is linked to unfavorable ...

Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.

Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading to complications such as retinopathy, nephropathy,...

Incorporating the STOP-BANG questionnaire improves prediction of cardiovascular events during hospitalization after myocardial infarction.

Obstructive sleep apnea (OSA) may impact outcomes in acute coronary syndrome (ACS) patients. The Global Registry of Acute Coronary Events (GRACE) scor...

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 model using contrast-enhanced ultrasound (CEUS) ra...

Cross-organ hierarchy of HLA molecular mismatches in donor-specific antibody development in solid organ transplantations.

Donor-specific antibodies (DSAs) against human leukocyte antigen (HLA) play a crucial role in antibody-mediated rejection, a major barrier to successf...

One-Drop Serum Screening Test to Monitor Tissue Iron Accumulation.

Although iron is an essential element for vital body functions, iron overload (IO) is accompanied by significant cellular damage due to its accumulati...

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 like proliferation and transport, thereby they beco...

Radiomics-based differentiation of upper urinary tract urothelial and renal cell carcinoma in preoperative computed tomography datasets.

BACKGROUND: To investigate a non-invasive radiomics-based machine learning algorithm to differentiate upper urinary tract urothelial carcinoma (UTUC) ...