Urology

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 an...

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 significa...

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 prostat...

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 (PS...

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 ...

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 u...

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 pheno...

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, ...

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-we...

Prostate Cancer Screening in the MR Imaging Era: Evidence, Strategies, and Future Directions.

Prostate cancer screening has entered a new era with the integration of MR imaging and artificial in...

The association between ZJU index and kidney stone risk: a machine learning approach on NHANES 2007-2018.

Efficient Deep Ladle-Net for fast universal 3D lesion segmentation on chest-abdomen-pelvis computed tomography.

Accurate evaluation of tumor size on follow-up computed tomography (CT) scans is critical for assess...

Nephropathy 1 Formula (N1F) mitigates cisplatin-induced acute kidney injury by inhibiting TAK1-dependent NF-κB signaling.

ETHNOPHARMACOLOGICAL RELEVANCE: Nephropathy 1 Formula (N1F) derives from the classical traditional C...

PTCMIL: multiple instance learning via prompt token clustering for whole slide image analysis.

Multiple Instance Learning (MIL) has achieved significant success in whole slide image (WSI) analysi...

Endothelial SMAD1-MCAM axis facilitates sunitinib resistance and progression of clear cell renal cell carcinoma via LAMB1-ITGB1 signaling.

Clear cell renal cell carcinoma (ccRCC) is characterized by high metastatic potential and frequent r...

Meta learning optimized TabNet for small sample repeat prostate biopsy prediction.

PURPOSE: Repeat prostate biopsy prediction remains limited by small patient cohorts that constrain a...

Hybrid Multi-View MRI Fusion for csPCa Diagnosis via Intra- and Inter-View Transformers.

Accurate diagnosis of clinically significant prostate cancer (csPCa) from multi-view MRI scans (axia...

MedFusion-gP-AKI: development and multicenter validation of a machine learning fusion model for early prediction of KDIGO stage 3 acute kidney injury in critically ill traumatic cervicothoracic spinal cord injury patients.

KDIGO stage-3 acute kidney injury (AKI), a life-threatening complication in critically ill patients ...

Inter-observer variability in radiotherapy contouring with the use of autocontouring software: A systematic review.

Inter-observer variability (IOV) in radiotherapy contouring remains a significant source of uncertai...

Multiphase CT-based deep learning radiomics nomogram models for preoperative WHO/ISUP grading of clear cell renal cell carcinoma: a two-center validation study.

BACKGROUND: Preoperative determination of clear cell renal cell carcinoma (ccRCC) World Health Organ...

Empirical evaluation of variability and multi-institutional generalizability of deep learning survival models: application to renal cancer CT scans.

Deep learning survival (DLS) modeling has shown significant promise across multiple disease conditio...