Urology

Deep learning for quality assessment of axial T2-weighted prostate MRI: a tool to reduce unnecessary rescanning.

BACKGROUND: T2-weighted images are a critical component of prostate magnetic resonance imaging (MRI), and it would be useful to automatically assess image quality (IQ) on a patient-specific basis without radiologist oversight.

A deep-learning algorithm using real-time collected intraoperative vital sign signals for predicting acute kidney injury after major non-cardiac surgeries: A modelling study.

BACKGROUND: Postoperative acute kidney injury (PO-AKI) prediction models for non-cardiac major surgeries typically rely solely on preoperative clinical characteristics.

MED-NCA: Bio-inspired medical image segmentation.

The reliance on computationally intensive U-Net and Transformer architectures significantly limits their accessibility in low-resource environments, c...

Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study.

BACKGROUND: Persistent sepsis-associated acute kidney injury (SA-AKI) shows poor clinical outcomes and remains a therapeutic challenge for clinicians....

Implementing large language model and retrieval augmented generation to extract geographic locations of illicit transnational kidney trade.

BACKGROUND: Illicit kidney trade networks, operating globally, involve intricate interactions among various players, most notably buyers, sellers, bro...

Prediction of acute and chronic kidney diseases during the post-covid-19 pandemic with machine learning models: utilizing national electronic health records in the US.

BACKGROUND: COVID-19 has been linked to acute kidney injury (AKI) and chronic kidney disease (CKD), but machine learning (ML) models predicting these ...

Risk Prediction Models for Contrast-associated Acute Kidney Injury After Percutaneous Coronary Intervention: A Systematic Review.

The aim of this review was to systematically review published studies on risk prediction models for contrast-associated acute kidney injury (CA-AKI) i...

Circulating miRNAs in genitourinary cancer: pioneering advances in early detection and diagnosis.

MicroRNAs (miRNAs) are noncoding, single-stranded RNAs molecules modulating gene expression thanks to their ability to bind mRNAs. Indeed, they regula...

A population based optimization of convolutional neural networks for chronic kidney disease prediction.

Chronic kidney disease (CKD) is a global public health concern, and the timely detection of the disease is priceless. Most of the classical machine le...

AI-generated questions for urological competency assessment: a prospective educational study.

BACKGROUND: The integration of artificial intelligence (AI) in medical education assessment remains largely unexplored, particularly in specialty-spec...

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study.

PURPOSE: Anti-PD-1 antibodies are widely used for cancer treatment, including in advanced renal cell carcinoma (RCC). However, the therapeutic respons...

Advancing Cardiovascular, Kidney, and Metabolic Medicine: A Narrative Review of Insights and Innovations for the Future.

Cardiovascular, kidney and metabolic (CKM) conditions are interrelated, significantly contributing to morbidity, mortality and healthcare burden. Desp...

Timing of kidney replacement therapy in critically ill patients: A call to shift the paradigm in the era of artificial intelligence.

Acute kidney injury (AKI) is a common condition in intensive care units (ICUs) and is associated with high mortality rates, particularly when kidney r...

Using deep learning generated CBCT contours for online dose assessment of prostate SABR treatments.

Prostate Stereotactic Ablative Body Radiotherapy (SABR) is an ultra-hypofractionated treatment where small setup errors can lead to higher doses to or...

Association of acute kidney injury with 1-year mortality in granulomatosis with polyangiitis patients: a cohort study using mediation analyses and machine learning.

To investigate the correlation between acute kidney injury (AKI) and 1-year mortality in patients with granulomatosis with polyangiitis (GPA). Clinica...

A semi-supervised prototypical network for prostate lesion segmentation from multimodality MRI.

Prostate lesion segmentation from multiparametric magnetic resonance images is particularly challenging due to the limited availability of labeled dat...

A machine learning toolkit assisted approach for IMRT fluence map optimization: feasibility and advantages.

. Traditional machine learning (ML) and deep learning (DL) applications in treatment planning rely on complex model architectures and large, high-qual...

Machine learning modeling and multi objective optimization of artificial detrusor.

To address the problem of obtaining optimal design parameters for existing artificial detrusors using single-objective optimization methods, this rese...

Development of explainable artificial intelligence based machine learning model for predicting 30-day hospital readmission after renal transplantation.

BACKGROUND: Hospital readmission following renal transplantation significantly impacts patient outcomes and healthcare resources. While machine learni...

Advancing personalized, predictive, and preventive medicine in bladder cancer: a multi-omics and machine learning approach for novel prognostic modeling, immune profiling, and therapeutic target discovery.

OBJECTIVE: This study aimed to identify and analyze immunogenic cell death (ICD)-related multi-omics features in bladder cancer (BLCA) using single-ce...