Urology

C-reactive protein-triglyceride-glucose index and incident mild cognitive impairment among patients with cardiovascular-kidney-metabolic syndrome: a dual-cohort prediction and double machine learning analysis.

PURPOSE: Develop an interpretable machine learning model and evaluate the predictive and potential c...

Pre-diagnosis plasma cell-free DNA reveals early signatures of prostate and breast cancer risk up to eight years prior to clinical detection.

Genome-wide cell-free DNA (cfDNA) methylation profiling of 491 pre-diagnosis breast and prostate can...

S100A8/A9-TMEM24 axis drives podocyte injury by impairing autophagy: a novel theranostic target for early diabetic nephropathy.

OBJECTIVE: To establish a comprehensive theranostic framework for early-stage diabetic kidney diseas...

Task-agnostic explainable contrastive learning model for malignant cell detection in urine cytology.

Bladder cancer remains one of the most prevalent urological malignancies, where early detection is c...

Development and evaluation of a combined machine learning model for the prediction of acute GU toxicity in prostate cancer radiotherapy.

PURPOSE: To develop and internally evaluate a compact multimodal machine learning model for predicti...

Artificial intelligence in onco-anaesthesia: Current applications, challenges, and future directions.

Artificial intelligence (AI) is transforming onco-anaesthesia by shifting practice from reactive phy...

Comment on: "deep learning augmented pathological grading and intraductal carcinoma of the prostate signatures improve recurrence prediction after intensity-modulated radiation therapy".

An explainable hybrid SMPR-Net-XGBoost framework for automated lupus nephritis detection using medical image analysis.

Lupus Nephritis (LN) is among the worst renal manifestations of Systemic Lupus Erythematosus (SLE) t...

Quantitative MRI for World Health Organisation/International Society of Urological Pathology Grading of Renal Cell Carcinoma: a systematic review and diagnostic meta-analysis.

OBJECTIVES: To synthesise evidence on quantitative MRI biomarkers for predicting World Health Organi...

Continuous-Time Transformer with Adaptive Mutation-Locking for Early Prediction of Acute Kidney Injury.

OBJECTIVE: Accurate early prediction of acute kidney injury is critical, yet existing deep learning ...

Deep learning-enabled screening of chronic kidney disease from echocardiography.

BACKGROUND: Chronic kidney disease (CKD) affects nearly 850 million individuals globally. The preval...

Transcriptomics-informed systems toxicology prioritizes candidate links between endocrine-disrupting chemicals and chronic kidney disease.

Endocrine-disrupting chemicals (EDCs) are environmentally relevant chemicals that may contribute to ...

Leveraging time-series electronic health records with large language models for chronic kidney disease diagnosis in primary care.

OBJECTIVES: Chronic kidney disease (CKD) presents a growing public health challenge in China, exacer...

Radiomics and Deep Learning Models Based on Manual and Semi-automatic Segmentation of Ultrasound Images for HER2 Prediction in Bladder Cancer.

RATIONALE AND OBJECTIVES: To evaluate semi-automatic segmentation of bladder ultrasound images and d...

Current status and future directions of AI in prostate cancer detection on MRI: a special report from the ESUR prostate MRI working group authors.

This report from the ESUR Prostate MRI Working Group assesses the current role of artificial intelli...

Single-cell transcriptomics combined with Mendelian randomization reveals the pivotal role of WDR83OS in clear cell renal cell carcinoma: An observational and bioinformatic study.

This study aimed to comprehensively investigate the molecular mechanisms of clear cell renal cell ca...

Clinical efficacy of AI-navigated transperineal MRI-TRUS fusion biopsy for prostate cancer diagnosis: A retrospective cohort study.

This study evaluates the clinical efficacy of transperineal 3D image registration combined with AI-e...

Explainable artificial intelligence for predicting mortality in geriatric patients undergoing hip arthroplasty: Machine learning analysis using national health insurance data.

We performed machine learning analysis of population data to determine the major determinants of 1-y...

Artificial intelligence and machine learning in transplantation surgery care pathway.

Artificial intelligence (AI) and machine learning (ML) are increasingly applied across the transplan...

Machine perfusion distribution across clinical phenotypes in kidney transplantation: A national cohort study using unsupervised clustering.

BACKGROUND: Unsupervised machine learning identifies clinically meaningful subgroups across biomedic...

Multimodal large language models for bladder tumor detection in cystoscopy: a retrospective benchmarking study.

PURPOSE: Cystoscopic assessment is central to bladder cancer diagnosis, yet visual interpretation re...