Urology

Bioinspired hybrid optimisation and deep belief neural networks for early chronic kidney disease detection: an explainable clinical AI framework.

The early detection of chronic kidney disease (CKD) can lead to timely and appropriate clinical intervention. However, most CKD diagnostic systems rely on redundant features and provide unreliable results in small and unbalanced datasets. Therefore, it is challenging to apply them in clinical settings due to a lack of transparency, as well as the extensive amount of time and effort to fine-tune th...

Transformer-based prediction of radiotherapy couch shift risk in prostate cancer based on rectal volume.

Development and Validation of an Automated Pediatric Cancer Staging Calculator Using the Toronto Pediatric Cancer Stage Guidelines.

BACKGROUND: Pediatric cancer stage at diagnosis is critical for prognosis and research comparisons. The Toronto Pediatric Cancer Stage Guidelines stan...

Study of bladder cancer detection in standard white light versus AI-supported endoscopy-01 (RAISE-01) - Development and validation of an AI-based support tool.

BACKGROUND: Diagnosis and surveillance of bladder cancer rely on white-light cystoscopy (WLC). However, this modality is operator-dependent and associ...

Free Energy Calculation Method Based on Enhanced Sampling of Diverse Protein Conformations Predicted by Artificial Intelligence.

Recent advances in artificial intelligence (AI) have enabled the rapid and accurate prediction of diverse protein structures. The predicted conformati...

PETWB-REP: A Multi-Cancer Whole-Body FDG PET/CT Dataset with Corresponding Radiology Reports.

Publicly available, large-scale medical imaging datasets are crucial for developing and validating artificial intelligence (AI) models and conducting ...

Prostate MRI quality improvement: a Roadmap from the ESUR Prostate MRI Working Group.

Prostate magnetic resonance imaging (MRI) has become a crucial tool in diagnosing and managing prostate cancer, mainly by helping to avoid unnecessary...

Refining prognostication in non-muscle-invasive bladder cancer: From clinical models to artificial intelligence.

Over the past 2 decades, risk stratification in non-muscle-invasive bladder cancer (NMIBC) has evolved considerably, progressing from simple clinico-p...

Systematic evaluation of single-cell multimodal data integration enhances cell type resolution and discovery of clinically relevant states in complex tissues.

BACKGROUND: The integration of multimodal single-cell data enables comprehensive organ reference atlases, yet its impact remains largely unexplored, p...

Robotic credentialing and simulation-based training: An institutional perspective.

INTRODUCTION: Simulation-based training has emerged as a critical tool in the acquisition of robotic surgical skills, especially in urology, where pro...

Comparison between artificial intelligence-based and manual organ delineations in pretreatment computed tomography scans of prostate cancer patients: a visual grading study.

This study aimed to evaluate the clinical acceptability of artificial intelligence (AI)-based organ segmentations on pretreatment CT images of prostat...

Lung cancer as a global health challenge: Multidimensional biomarker research and therapeutic advances.

Lung cancer, the leading cause of global cancer-related mortality, is categorized into small-cell and non-small-cell subtypes. The heterogeneous non-s...

Immune-activated & pathology-characterized: the distinct clear cell renal cell carcinoma subtypes for 3PM strategies derived from artificial intelligence in multi-omics.

BACKGROUND AND OBJECTIVE: Renal clear cell carcinoma (ccRCC) is highly heterogeneous, with significant differences in clinical outcomes such as progno...

Foundation Model and Multi-Instance Learning-Based Framework for Predicting Lymphovascular Invasion in Prostate Cancer.

BACKGROUND: Lymphovascular invasion (LVI) is a well-established adverse prognostic factor in prostate cancer (PCa). This study aimed to develop and va...

Language-Related Functional Connectivity in Post-Stroke Aphasia: Preliminary Findings from a Graph-Theoretical and Interpretable Machine Learning Study.

PURPOSE: To have an insight into language-related functional connectivity in post-stroke aphasia (PSA) from graph theory measurements when performing ...

Association of the estimated glucose disposal rate combined with a body shape index with all-cause and cardiovascular-specific mortality among individuals with cardiovascular-kidney-metabolic syndrome.

BACKGROUND: Individuals with cardiovascular-kidney-metabolic (CKM) syndrome exhibit a substantially elevated risk of all-cause and cardiovascular-spec...

CT-based radiomics for predicting the treatment response to PD-1/PD-L1 inhibitors combined with chemotherapy in unresectable gastric cancer.

OBJECTIVE: To develop and validate a CT-based radiomics model to predict immunotherapy response in unresectable gastric cancer and explore its underly...

Photon-counting CT-enabled urolithiasis phenotyping: virtual non-iodine reconstructions, automated measurement, and spectral radiomics.

PURPOSE OF REVIEW: Urolithiasis management increasingly depends on accurate, noninvasive stone phenotyping to guide acute intervention, secondary prev...

24-hour physical activity, sedentary behaviour and sleep profiles in individuals with cancer: a UK Biobank cohort study.

BACKGROUND: Behaviours across a 24-hour day, including physical activity, sedentary time and sleep, are disrupted following cancer and contribute to c...

PCa-Mamba: Spatiotemporal state space models for prostate cancer detection in multi-parametric MRI.

Multiparametric Magnetic Resonance Imaging (mpMRI), including T2-weighted imaging (T2), diffusion-weighted imaging (DWI), and dynamic contrast-enhance...