Nephrology

Characterizing prognostic and immunological traits of kidney renal clear cell carcinoma via mitochondria-associated membranes and identifying DNM1L as a potential therapeutic target using machine learning.

MYO1C is a urinary extracellular vesicle biomarker and mediator of podocyte injury in diabetic nephropathy.

Type 2 diabetic nephropathy (T2DN) is a major complication of type 2 diabetes and a leading cause of chronic kidney disease. This study aimed to explore MYO1C as both a candidate biomarker and elucidate its role as a mechanistic mediator of podocyte injury in T2DN. Using urinary extracellular vesicle RNA biomarkers identified from a training and validation cohort of 33 type 2 diabetes and 40 T2DN ...

How do chronic diseases affect personal and household income? A double debiased machine learning analysis of the China health and retirement longitudinal study (CHARLS) in older adults.

OBJECTIVES: This study aimed to investigate the impacts of chronic diseases such as hypertension, dyslipidaemia and diabetes on personal and household...

The discordance of remnant cholesterol and low-density lipoprotein cholesterol as a predictor of diabetes, diabetic microvascular diseases, and cardiovascular disease.

BACKGROUND: The impact of discordance between remnant cholesterol (RC) and low-density lipoprotein cholesterol (LDL-c) on diabetes, diabetic kidney di...

Numerical modeling and prediction of late estimated glomerular filtration rate in kidney transplant recipients based on machine learning models and the Monte Carlo simulation method.

OBJECTIVES: This paper presents an experimental numerical method for modeling and analyzing stochastic systems. For this purpose, various machine pred...

Training and external validation of machine learning supervised prognostic models of upper tract urothelial cancer (UTUC) after nephroureterectomy.

Machine learning-driven prediction model for successful weaning of patients from mechanical ventilation in ICU.

BACKGROUND: Mechanical ventilation is a critical life support technology in the intensive care unit. However, the weaning process remains complex, mak...

A machine learning approach for predicting osmotic coefficients and deriving activity coefficients in alkyl ammonium salts.

Quaternary Ammonium Salts (Quats) have diverse applications across various domains. They are extensively used as phase-transfer catalysts (PTCs) in ch...

Longitudinal Peripheral Blood Transcriptomics Reveal Novel Signatures During Cardiac Allograft Rejection.

BACKGROUND: Acute cellular rejection (ACR) remains a major cause of morbidity after heart transplantation despite advances in immunosuppression. Whole...

Acetyl tributyl citrate as a new risk factor for osteoporosis: An integrated study from multi-level toxicological assessment and experimental validation.

This study aimed to elucidate the toxicological effects and underlying mechanisms of the plasticizer acetyl tributyl citrate (ATBC) on osteoporosis (O...

Validation of histopathology-based deep learning algorithms for detection of actionable non-small cell lung cancer biomarkers.

Non-small cell lung cancer (NSCLC) patient management relies on molecular analysis to determine eligibility for targeted therapy. Furthermore, neoadju...

Subphenotype Identification for Sepsis-Associated Acute Kidney Injury Using Graph Bidirectional Mamba Networks.

Sepsis-associated acute kidney injury (SA-AKI) is a heterogeneous clinical syndrome and a leading cause of mortality in intensive care units (ICUs). I...

Adaptive geometric-attention multi-task framework with knowledge distillation for aortic dissection detection in non-contrast CT.

Aortic dissection (AD) is a life-threatening cardiovascular emergency. Non-contrast-enhanced CT (NCE-CT) could provide timely AD screening with fewer ...

Preoperative Neuroimaging Markers, Clinical Severity Measures, and Shunt Characteristics for Predicting Shunt Revision in Idiopathic Intracranial Hypertension: An Explainable Machine-Learning Study.

BACKGROUND AND PURPOSE: Surgical shunt placement is a common treatment for idiopathic intracranial hypertension (IIH) but is hampered by high revision...

Leveraging machine learning to predict de novo skin malignancy following lung transplantation.

AIMS: This study aimed to predict post-transplant malignancy risks at multiple levels among lung transplant recipients using machine learning (ML) and...

MCDNet: Morphological-conditional dual-view fusion for 3D tubular structure segmentation.

Accurate segmentation of 3D tubular structures in medical images is critical for clinical diagnosis and interventional planning. Although deep learnin...

Machine Learning Prediction of Chronic Kidney Disease in Elderly MetS Patients Using NHANES 2011-2020 Data.

BACKGROUND: Chronic kidney disease (CKD) is getting more common in elderly people with metabolic syndrome, but early detection and risk prediction are...

Systemic Microvasculature Frailty: Brain frailty score predicts contrast-associated acute kidney injury after thrombectomy for stroke.

BACKGROUND: Contrast-associated acute kidney injury (CA-AKI) is a frequent complication after mechanical thrombectomy (MT). Cerebral small vessel dise...

A chronic kidney disease prediction system based on Internet of Things using walrus optimized deep learning technique.

The Internet of Things (IoT) and cloud computing (CC) concepts are commonly incorporated in healthcare applications. In the healthcare industry, a hug...

The Macroevolution of Filamentation Morphology Across the Saccharomycotina Yeast Subphylum.

Saccharomycotina are a subphylum of ascomycete fungi with diverse asexual growth morphologies. Filamentous growth can comprise linear and branched bud...