Urology

Predicting kidney graft survival with a machine learning model based on for-cause biopsy transcriptomics.

Kidney transplantation significantly improves outcomes in end-stage renal disease, however, long-term graft survival remains suboptimal. Traditional prognostic models often yield limited predictive power. Given the routine use of for-cause biopsies in clinical practice, we aimed to develop and compare ML models to predict graft survival using gene expression profiles from indication biopsies. Data...

High-throughput multi-camera array microscope platform for automated 3D behavioral analysis of swimming zebrafish larvae.

Understanding the behavioral and morphological dynamics of moving model organisms like the zebrafish larvae requires accurate, high-throughput 3D analysis. However, traditional single-view 2D video tracking fails to capture the full scope of natural 3D movements and postural dynamics. Here, we present a novel high-throughput 24-camera array microscope with a co-designed "mirrored well plate" that ...

Prediction of renal cell carcinoma: Development and validation of machine learning model.

Renal cell carcinoma (RCC) is the leading cause of urinary system morbidity and mortality. Early identification is crucial for improving RCC patient o...

An exploratory study on the relationship between renal cell carcinoma and CAFs infiltration by integrating Pathomics and collagen features.

OBJECTIVE: Cancer-associated fibroblasts (CAFs) are a critical component of the tumor microenvironment and play a significant role in renal cell carci...

Accuracy, readability, and understandability of EAU guidelines bot for testicular cancer.

PURPOSE: Recently, the EAU guidelines presented the EAU guidelines bot to assist urologists in the reading of the guidelines; however, up to date, no ...

Coriandrum sativum improves prognosis in clear cell renal cell carcinoma by targeting NEK6 to modulate the immune microenvironment: a predictive study based on network pharmacology and multi-omics analysis.

Coriandrum sativum L. (coriander) is a medicinal herb with diverse pharmacological properties, but its molecular mechanism in clear cell renal cell ca...

Chronic kidney disease detection using XceptionNet with Harmonic Addax Optimization.

Chronic Kidney Disease (CKD) refers to a persistent and progressive impairment of kidney function occurring over a prolonged duration. Impaired kidney...

Comment on Machine learning survival analysis for predicting kidney disease progression in patients with acute kidney injury undergoing continuous kidney replacement therapy: An analysis of the LINKA database.

Endocrine and metabolic determinants of cardiometabolic risk in mild autonomous cortisol secretion.

BACKGROUND: Benign adrenal tumours, found in 1-7% of adults, can be non-functioning (NFAT) or show mild autonomous cortisol secretion (MACS), i.e., bi...

The Future of Non-muscle-invasive Bladder Cancer: Towards a Molecular-Digital Paradigm for Personalized Management.

The management of non-muscle-invasive bladder cancer (NMIBC) is undergoing a major paradigm shift driven by molecular biomarkers, artificial intellige...

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 explo...

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...

Letter to the Editor on "Research on the auxiliary diagnosis of male neurogenic lower urinary tract dysfunction based on a deep-learning algorithm".

Spatial-Spectral Deep Learning for Prostate Cancer Tissue Classification in Infrared Spectroscopy.

Modern methods of infrared (IR) spectroscopy yield full IR absorbance spectra in arrays, forming hyperspectral images. End-to-end processing of these ...

Towards robust deep learning-based autosegmentation in MRI-planned gynecological brachytherapy: Importance of scalable development and comprehensive evaluation.

PURPOSE: To present comprehensive development and evaluation methodologies for a generalizable deep learning (DL)-driven autocontouring model of stand...

Semantic segmentation deep learning model boosts surgeons' organ recognition in minimally invasive hysterectomy - a prospective multi-center reader performance study using pre-selected video clips.

BACKGROUND: Injury to the ureter and bladder during minimally invasive hysterectomy remains a serious complication, often resulting from insufficient ...

Integrated Ultrasound Device for Precision Bladder Volume Monitoring via Acoustic Focusing and Machine Learning.

Bladder volume monitoring is critical for managing lower urinary tract dysfunctions, yet existing methods remain invasive or operator-dependent and ar...

Comment on "Clinical management implications from 33,579 urinary stones: novel patterns in composition, comorbidities, seasonal variation, and machine learning-based urosepsis prediction".

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...