Urology

Radiomics for the Prediction of Postoperative Chronic Kidney Disease in Renal Tumor Patients undergoing Surgical Resection.

OBJECTIVE: Chronic kidney disease (CKD) is a significant concern following renal tumor surgery, impacting long-term renal function and patient outcomes. This study investigates the potential of CT-based radiomics as a quantitative imaging approach to predict postoperative CKD in kidney tumor patients. METHODS: We included adult patients with renal tumor surgery treated at our center between 2012 a...

Generative AI Chatbots as Digital Adjuncts for Sexual Health Information After Prostate Cancer in Men Who Have Sex With Men: Auto-Netnographic Study.

BACKGROUND: Sexual health concerns following prostate cancer treatment are common yet often insufficiently addressed in clinical practice, particularly among men who have sex with men. These individuals may face additional barriers stemming from heteronormative assumptions, limited disclosure, and a lack of culturally tailored information. As generative artificial intelligence (GenAI) chatbots bec...

Noninvasive preoperative risk stratification of prostate cancer via a foundational model based deep learning with PSMA PET/CT.

Risk prediction in IgA nephropathy: from conventional models to machine learning, deep learning, and precision nephrology.

IgA nephropathy (IgAN) is the most prevalent primary glomerular disease worldwide and a leading cause of end-stage kidney disease (ESKD). Its clinical...

UriPred: Machine learning prediction of urinary proteins and identification of biomarkers for liver cancer.

Urinary proteins are promising non-invasive biomarkers, but their low abundance and wide dynamic range make detection challenging. This study presents...

Urinary metal exposure, systemic inflammation, and advanced cardiovascular-kidney-metabolic syndrome risk in US adults.

To examine inflammatory biomarkers as potential mediators in the association between urinary metal exposure and advanced Cardiovascular-Kidney-Metabol...

Spectral CT-derived extracellular volume fraction for pathological characterization and noninvasive T staging in colon cancer.

OBJECTIVES: To investigate the association between the extracellular volume fraction (ECV) quantified by spectral CT and multiparameter pathological f...

Development and internal validation of machine learning in predicting prognosis of acute kidney injury patients in resource-limited setting.

BACKGROUND: Machine learning models for predicting acute kidney injury (AKI) prognosis have primarily been developed in resource-rich settings, with l...

ALKBH5 orchestrates ferroptosis-driven tumor suppression: An LLM-powered discovery in prostate cancer.

The treatment of prostate cancer (PCa) continues to pose substantial clinical challenges. The use of large language models (LLMs) to identify the key ...

Deep Learning Artificial Intelligence and Restriction Spectrum Imaging for Patient-level Detection of Clinically Significant Prostate Cancer on Biparametric Magnetic Resonance Imaging.

BACKGROUND AND OBJECTIVE: Our aim was to evaluate whether combining the maximum restriction score derived from restriction spectrum imaging (RSIrsmax)...

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".

Machine learning models for identifying urinary incontinence in women with a history of hysterectomy using basic demographic and clinical characteristics: A cross-sectional study.

BACKGROUND: Urinary incontinence (UI) in women with a history of hysterectomy represents a significant global health concern. It is crucial to clarify...

Using human-robot interaction to assess emotion recognition in dialysis patients: A preliminary study.

This cross-sectional observational study examined the relationship between psychological factors and multimodal emotion recognition abilities in patie...

Ensuring reliable digital pathology: a comparative analysis of HistoQC and PathProfiler for artefacts detection in prostate whole-slide images.

BACKGROUND: Whole-slide images (WSIs) offer high-resolution views of tissue but are often compromised by artefacts that hinder human and AI interpreta...

Factors influencing long-term outcomes in lung transplantation: effective monitoring and comprehensive intervention.

PURPOSE OF REVIEW: Achieving long-term survival after lung transplantation remains a major challenge. Outcome determinants have expanded beyond pathop...

The role of artificial intelligence in improving patient communication and shared decision-making in urology: A systematic review.

BackgroundEffective communication and shared decision-making are essential for optimising urological care, making informed decisions, and improving pa...

Application and prospect of artificial intelligence in diagnostic imaging of prostate cancer.

Prostate cancer is a leading cause of male cancer mortality, and early, accurate diagnosis is critical. Artificial intelligence (AI), including machin...

ASO Visual Abstract: Deep Learning-Based Multimodal Clinico-Histology-Genomic Prognostic Model in Prostate Cancer.

Atomically Precise Metal Clusters for NIR-II Imaging.

ConspectusNear-infrared II (NIR-II, 1000-3000 nm), also defined as shortwave infrared (SWIR) imaging, offers reduced light scattering and low tissue a...

Explainable machine learning-based 28-day mortality prediction model for elderly patients with acute kidney injury.

Elderly patients with acute kidney injury (AKI) face a significantly increased mortality risk. Recent advances in machine learning technology have mad...