Urology

Artificial intelligence in prostate cancer.

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, ...

Utilizing Predictive Analytics to Understand Neurogenic Bladder Symptom Score (NBSS) Variations in Adults With Acquired Spinal Cord Injury.

INTRODUCTION: Individuals with spinal cord injury (SCI) have varying bladder health trajectories after their injury. We explored whether a predictive machine learning model could identify which variables impact urinary symptoms.

Predicting time-to-first cancer diagnosis across multiple cancer types.

Cancer causes over 10 million deaths annually worldwide, with 40.5% of Americans expected to be diagnosed in their lifetime. Early detection is critic...

Prediction model for postoperative urinary retention in patients undergoing totally extraperitoneal groin hernia repair.

BACKGROUND: Postoperative urinary retention remains a common complication after totally extraperitoneal groin hernia repair, often prolonging hospital...

Analysis of Single-Cell RNA-Seq Data to Investigate Tumor Cell Heterogeneity in Uroepithelial Bladder Cancer and Predict Immunotherapy Response.

BACKGROUND: Numerous studies have suggested a close association between cancer stem cells (CSCs) and the tumor microenvironment (TME), suggesting that...

Lossy DICOM conversion may affect AI performance.

Many pathologies have started to digitize their glass slides. To ensure long term accessibility, it is desirable to store them in the DICOM format. Cu...

A novel method to predict the haemoglobin concentration after kidney transplantation based on machine learning: prediction model establishment and method optimization.

BACKGROUND: Anaemia is a common complication after kidney transplantation, and the haemoglobin concentration is one of the main criteria for identifyi...

A practical guide for nephrologist peer reviewers: evaluating artificial intelligence and machine learning research in nephrology.

Artificial intelligence (AI) and machine learning (ML) are transforming nephrology by enhancing diagnosis, risk prediction, and treatment optimization...

Cellular senescence in renal ischemia-reperfusion injury.

Acute kidney injury (AKI) affects more than 20% of hospitalized patients and is a significant contributor to morbidity and mortality, primarily due to...

External Validation on a Japanese Cohort of a Computer-Aided Diagnosis System Aimed at Characterizing ISUP ≥ 2 Prostate Cancers at Multiparametric MRI.

OBJECTIVE: To evaluate the generalizability of a computer-aided diagnosis (CADx) system based on the apparent diffusion coefficient (ADC) and wash-in ...

Development and retrospective validation of an artificial intelligence system for diagnostic assessment of prostate biopsies: study protocol.

INTRODUCTION: Histopathological evaluation of prostate biopsies using the Gleason scoring system is critical for prostate cancer diagnosis and treatme...

Multiple omics-based machine learning reveals peripheral blood immune cell landscape during acute rejection of kidney transplantation and constructs a precise non-invasive diagnostic strategy.

Kidney transplantation is the optimal treatment for end-stage renal disease (ESRD), but acute rejection (AR) remains a major factor affecting graft su...

Association of dietary quality, biological aging, progression and mortality of cardiovascular-kidney-metabolic syndrome: insights from mediation and machine learning approaches.

BACKGROUND: To investigate the association between the Dietary Inflammatory Index (DII), biological aging, and the staging and mortality of cardiovasc...

Performance of GPT-4 for automated prostate biopsy decision-making based on mpMRI: a multi-center evidence study.

BACKGROUND: Multiparametric magnetic resonance imaging (mpMRI) has significantly advanced prostate cancer (PCa) detection, yet decisions on invasive b...

Identification and validation of parthanatos-related genes in end-stage renal disease.

BACKGROUND: End-Stage Renal Disease (ESRD) is a severe chronic kidney disease with a rising global incidence, often accompanied by various complicatio...

Machine learning models to predict the zero-fragment rate and lower pole access with FANS during flexible Ureteroscopy-an EAU section of endourology study.

INTRODUCTION: Suction devices such as flexible and navigable suction ureteral access sheath (FANS) are promising tools to reach the zero-fragment rate...

Interpretable machine learning models for survival prediction in prostate cancer bone metastases.

Prostate cancer bone metastasis (PCBM) is a highly lethal condition with limited survival. Accurate survival prediction is essential for managing thes...

Identification of inflammation-related biomarkers and therapeutic targets for neurogenic bladder fibrosis via multi-omics analysis.

Inflammatory responses play a crucial role in the progression of pediatric neurogenic bladder (NB)-associated fibrosis; however, their specific contri...

An integrated approach for key gene selection and cancer phenotype classification: Improving diagnosis and prediction.

The identification of key features and reliable phenotype classification remains pivotal in cancer research, with direct implications for early diagno...

Robot-Assisted Retrograde Intrarenal Surgery: A Mini Review of the Literature on Robotic Surgery Platforms for Endoscopic Stone Surgery.

Retrograde intrarenal surgery (RIRS) has become a cornerstone in renal stone management, with robotic platforms recently entering clinical practice. T...