Urology

Identifying PLAU as a shared pathogenic gene in type 2 diabetes and bladder urothelial carcinoma through integrated transcriptomic analysis and machine learning for diagnostic and therapeutic value.

Type 2 diabetes mellitus (T2DM) and bladder urothelial carcinoma (BLCA) are two kinds of diseases that seriously threaten human health. Their pathogenesis is complex and involves the interaction of multiple genes and multiple pathways. Recent epidemiological studies have shown that the risk of BLCA in patients with T2DM is significantly higher than that in non-diabetic people, suggesting that ther...

Multi-Omics Integration Reveals the Genetic Mechanisms of Periodontitis and Predicts Therapeutic Drugs.

BACKGROUND: Periodontitis is a chronic inflammatory disease driven by host immune dysregulation. However, the specific genetic regulatory mechanisms underlying this disease remain unclear. Identifying key molecular targets is crucial for precise therapeutic intervention. METHODS: This study integrated genome-wide association study (GWAS) summary statistics from the Gene-Lifestyle Interactions in D...

Preoperative Predictive Modeling of Recurrent Graft Failure: Development and Validation of a 12-Month Prognostic Tool in Kidney Transplant Recipients.

BACKGROUND: Kidney transplantation is among the most effective treatments for end-stage renal disease. However, kidney transplant (KT) recipients rema...

Computer-Interpretable Domain Knowledge for Drug-Induced Acute Kidney Injury: a Knowledge Graph Approach.

In this study, a Knowledge Graph (KG) for Drug-Induced Acute Kidney Injury (DAKI) was developed to provide structured and standardized knowledge about...

Deep-learning-based artificial intelligence approaches for grading and progression prediction of clear cell renal cell carcinoma.

The grading classification of clear cell renal cell carcinoma (CCRCC) is a crucial prognostic factor. However, manual observation can lead to subjecti...

Dynamic urinary proteomics integrates single-cell and spatial transcriptomics to reveal tumour microenvironment and predict immunotherapy response in biliary tract cancer.

BACKGROUND: Most patients with biliary tract cancer (BTC) do not derive durable clinical benefit (DCB) from immune checkpoint inhibitors (ICIs), under...

Multiscale Prediction of Tumor Micronecrosis and Progression in Clear Cell Renal Cell Carcinoma Based on Artificial Intelligence: A Multicenter Cohort Study.

RATIONALE AND OBJECTIVES: Tumor micronecrosis (TM) represents a critical pathological feature influencing the prognosis and surgical management of cle...

mFLIP: metabolic flux interval prediction.

BACKGROUND: Understanding cellular metabolism often involves an accurate estimation of metabolic fluxes-the rates at which metabolites are converted i...

Development and external validation of a machine learning model for predicting post-CABG acute kidney injury: insights from MIMIC database and real-world cardiac surgery cohort.

OBJECTIVE: Acute kidney injury (AKI) is a severe complication following coronary artery bypass grafting(CABG) While machine learning models trained on...

Preliminary evaluation of an AI-enhanced simulated interprofessional learning intervention for pharmacy students: a mixed-methods pilot study.

BACKGROUND: Interprofessional education (IPE) is vital for preparing pharmacy students for collaborative practice but is often constrained by logistic...

Development and interpretability of a machine learning-derived model for the identification of latent prostate cancer in patients initially diagnosed with benign prostatic hyperplasia: a retrospective cohort study.

BACKGROUND: Prostate cancer (PCa) is characterized by pronounced intratumoral heterogeneity and multifocality, presenting ongoing challenges for early...

An explainable predictive machine learning model of oxaliplatin induced peripheral neuropathy based on clinical data: a retrospective single center.

BACKGROUND: Oxaliplatin (OXA) is widely used in the treatment of gastrointestinal malignancies such as colorectal cancer. However, oxaliplatin-induced...

Predicting 5-Year Mortality in Non-Small-Cell Lung Cancer Using the Korean Central Cancer Registry: Model Development and Validation Study.

BACKGROUND: Non-small-cell lung cancer (NSCLC) is one of the most common cancers and a leading cause of cancer-related mortality, making prognostic pr...

Combining artificial intelligence analysis with expert mammogram reading: Determining the optimal AI positivity cut-off point for the French population-based breast cancer screening program.

PURPOSE: Artificial intelligence (AI) is increasingly explored as a complement to radiologists in population-based breast cancer screening, yet optima...

The atlas of abdominal organ remodeling in hepatocellular carcinoma patients: An artificial intelligence-based multicenter imaging study.

BACKGROUND: Morphological changes of abdominal organs in hepatocellular carcinoma (HCC) remain uncharacterized. This study aimed to automatically quan...

Impact of glycosylation position on flavonoid isomers' inhibition of breast cancer-associated enzyme CYP1B1.

Isomerism in natural flavonoids critically influences enzyme inhibitory activity, particularly toward cytochrome P450 enzymes. Mangiferin and isomangi...

Comment on "Machine learning model for predicting interfraction motion of the seminal vesicles in prostate cancer radiotherapy".

Performance of large language models in urological decision support: a guideline-based comparative evaluation in urolithiasis.

Large language models (LLMs) are increasingly investigated for their potential role in guideline-based clinical information support. However, their co...

Deep learning reconstruction improves appendix visualization on pediatric magnetic resonance imaging (MRI): a single-center experience.

BACKGROUND: Thin-slice MRI may improve appendix visualization in children with suspected appendicitis, but reducing slice thickness decreases signal-t...

A simple morphometric algorithm based on nuclear atypia features of invasive breast carcinoma: relationship with nuclear grade, Ki-67 level, and hormone receptor status.

Background With the widespread availability of whole-slide imaging, many studies have utilized digital images of hematoxylin and eosin (H&E)-stained b...