Urology

AI-Based Evaluation of Prostate MR Imaging at a Modern Low-field 0.55 T Scanner Compared to 3 T in a Screening Cohort.

PURPOSE: To evaluate the effect of lower field strength on quantitative apparent-diffusion-coefficient (ADC) values, contrast of the T2-weighted MR images and the performance of an AI-based segmentation.

A Universal Method for Fingerprinting Multiplexed Bacteria: Evolving Pruned Sensor Arrays via Machine Learning-Driven Combinatorial Group-Specificity Strategy.

Array-based sensing technology holds immense potential for discerning the intricacies of biological systems. Nevertheless, developing a universal strategy for simultaneous identification of diverse types of multianalytes and meeting the diagnostic needs of a range of multiclassified clinical diseases poses substantial challenges. Herein, we introduce a combination method for constructing sensor ar...

CNN-Based Kidney Segmentation Using a Modified CLAHE Algorithm.

This paper presents an enhanced approach to kidney segmentation using a modified CLAHE preprocessing method, aimed at improving image clarity and CNN ...

How to incorporate generative artificial intelligence in nephrology fellowship education.

Traditional nephrology education faces challenges due to expanding medical knowledge, case complexity, and personalized learning needs. Generative art...

Reliability and quality of information provided by artificial intelligence chatbots on post-contrast acute kidney injury: an evaluation of diagnostic, preventive, and treatment guidance.

OBJECTIVE: The aim of this study was to evaluate the reliability and quality of information provided by artificial intelligence chatbots regarding the...

Evaluating the dosimetric impact of deep-learning-based auto-segmentation in prostate cancer radiotherapy: Insights into real-world clinical implementation and inter-observer variability.

PURPOSE: This study aimed to investigate the dosimetric impact of deep-learning-based auto-contouring for clinical target volume (CTV) and organs at r...

Assessing the Efficacy and Clinical Utility of Artificial Intelligence Scribes in Urology.

OBJECTIVE: To assess the quality of artificial intelligence (AI) scribes and to evaluate their impact on urologic practice.

anti-cancer activity of siddha metallo-mineral formulation from Thanga uram with Hela cell lines.

The second most common malignant tumour in women worldwide, cervical cancer seriously jeopardizes their health. It has been established that a high-ri...

Evaluation and comparison of synthetic computed tomography algorithms with 3T MRI for prostate radiotherapy: AI-based versus bulk density method.

PURPOSE: Synthetic computed tomography (sCT)-algorithms, which generate computed tomography images from magnetic resonance imaging data, are becoming ...

UrologiQ: AI-based accurate detection, measurement and reporting of stones in CT-KUB scans.

Kidney stone disease is becoming increasingly common worldwide, with its prevalence increasing annually across all age groups, races, and geographic r...

Development, validation and economic evaluation of a machine learning algorithm for predicting the probability of kidney damage in patients with hyperuricaemia: protocol for a retrospective study.

INTRODUCTION: Accurate identification of the risk factors is essential for the effective prevention of hyperuricaemia (HUA)-related kidney damage. Pre...

Applying natural language processing to understand symptoms among older adult home healthcare patients with urinary incontinence.

INTRODUCTION: Little is known about the range and frequency of symptoms among older adult home healthcare patients with urinary incontinence, as this ...

Deep-Learning Model for Quality Assessment of Urinary Bladder Ultrasound Images Using Multiscale and Higher-Order Processing.

Autonomous ultrasound image quality assessment (US-IQA) is a promising tool to aid the interpretation by practicing sonographers and to enable the fut...

Deciphering the impact of senescence in kidney transplant rejection: An integrative machine learning and multi-omics analysis via bulk and single-cell RNA sequencing.

BACKGROUND: The demographic shift towards an older population presents significant challenges for kidney transplantation (KTx), particularly due to th...

Cross-shaped windows transformer with self-supervised pretraining for clinically significant prostate cancer detection in bi-parametric MRI.

BACKGROUND: Bi-parametric magnetic resonance imaging (bpMRI) has demonstrated promising results in prostate cancer (PCa) detection. Vision transformer...

American College of Surgeons survival calculator for biliary tract cancers: using machine learning to individualize predictions.

BACKGROUND: Although cancer prognosis is most commonly estimated by tumor stage, survival is multifactorial. Our objective was to develop an American ...

AI-assisted patient education: Challenges and solutions in pediatric kidney transplantation.

We are writing in response to the recent publication on the use of artificial intelligence, particularly ChatGPT, in generating educational materials ...

Bacteriophage-Activated DNAzyme Hydrogels Combined with Machine Learning Enable Point-of-Use Colorimetric Detection of Escherichia coli.

Developing cost-effective, consumer-accessible platforms for point-of-use environmental and clinical pathogen testing is a priority, to reduce relianc...

Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005-2018.

BACKGROUND: The intake of dietary antioxidants and glycolipid metabolism are closely related to chronic kidney disease (CKD), particularly among indiv...

Machine-Learning-Based Predictive Model for Bothersome Stress Urinary Incontinence Among Parous Women in Southeastern China.

INTRODUCTION AND HYPOTHESIS: Accurate identification of female populations at high risk for urinary incontinence (UI) and early intervention are poten...