Latest AI and machine learning research in urology for healthcare professionals.
Background: Calcium oxalate nephrolithiasis is the most common type of kidney stone disease. Dietary oxalate intake is an important modifiable factor. Assessing dietary oxalate exposure in clinical practice poses challenges due to limitations of traditional dietary recall tools and variability in food composition data. Artificial intelligence (AI) applications in mobile health may offer scalable s...
Kidney-function assessment relies on blood urea as a clinically informative metabolic marker; however, its dependence on venipuncture and centralised laboratory testing limits high-frequency monitoring and delays timely clinical intervention. Here, we report an integrated platform combining a wearable buffered microfluidic patch with a physiology-informed, data-driven calibration framework for rea...
Abstract Background Prostate cancer (PCa) diagnosis remains challenged by the limited specificity of prostate-specific antigen (PSA) testing, which ca...
Single-shot echo-planar prostate diffusion-weighted imaging (DWI) is frequently complicated by geometric distortions, which impact the ability to deri...
Clinical prostate multi-parametric MRI relies heavily on high-quality diffusion-weighted imaging (DWI), yet reading DWI is frequently compromised by g...
Patient-specific 3D reconstruction of pelvic organ geometry from MRI is important for pelvic floor modeling and downstream patient-specific analysis. ...
Objectives: This study investigates large language models (LLMs) for clinical entity projection across substantial textual transformation. Specificall...
Deep neural networks (DNNs) frequently fail to generalize to out-of-distribution (OOD) medical images because of variations in scanners and acquisitio...
Translating high-dimensional, spatially resolved molecular datasets into testable biological findings remains a major research bottleneck. Here, we pr...
Background: Rapid and accurate identification of urinary tract infection (UTI) pathogens is critical for effective treatment and combating antimicrobi...
Background and purpose: oART enables daily plan adaptation to interfraction anatomical variations, but cumulative dose estimation remains limited by D...
Deformable image registration (DIR) is widely used in radiotherapy for dose propagation and accumulation, but uncertainty in the underlying deformatio...
Biochemical recurrence (BCR) after radical prostatectomy is a critical endpoint in prostate cancer, yet risk stratification relies almost entirely on ...
Clear cell renal cell carcinoma (ccRCC) exhibits pronounced heterogeneity across WHO histological grades, yet systematic single-cell multi-omics studi...
Large language models (LLMs) such as ChatGPT are rapidly reshaping healthcare education and simulation-based training in non-technical skills (NTS), y...
Non-canonical HLA-presented peptides are promising therapeutic targets, but their low abundance makes them difficult to reproducibly identify and quan...
Our study evaluated whether a deep learning auto segmentation model combined with machine learning triage can streamline radiotherapy clinical trial q...
Phylogenetic inference is a common task in molecular and evolutionary biology and has conventionally required a multiple sequence alignment (MSA), a s...
Interobserver variability in pathological assessments is a well-recognized challenge that impacts diagnostic reliability and disease understanding. Th...
Background and Objective: Access to real-world electronic health records (EHRs) remains limited by privacy, governance and annotation constraints, hin...