Urology

Development and multicohort external validation of a preoperative [18F]PSMA-1007 PET-derived deep learning score and multimodal model for predicting biochemical recurrence-free survival after radical prostatectomy.

PURPOSE: To develop and validate a preoperative [18F]PSMA-1007 PET-derived deep learning score (DLS) and an integrated model combining DLS, D'Amico risk classification, and SUVmax for predicting biochemical recurrence-free survival (BRFS) after radical prostatectomy (RP). MATERIALS AND METHODS: This retrospective study included 697 patients with prostate cancer who underwent preoperative [18F]PSMA...

An interpretable machine learning model for predicting febrile seizures following enterovirus infection in children.

OBJECTIVE: This study aims to develop an interpretable machine learning model for predicting the risk of FS in children with enterovirus (EV) infections and to implement it for clinical application. METHODS: This retrospective study included 446 hospitalized children with EV infection (144 FS, 302 non‑FS). LASSO regression and BORUTA algorithm selected 15 key predictors from 53 clinical variables....

Scaling AI-enabled imaging-based screening: lessons from reporting for the NHS England lung cancer screening programme.

Lung cancer is the leading cause of cancer death globally, and low-dose computed tomography (LDCT) screening reduces lung cancer mortality. The NHS En...

Machine learning-based evaluation of lipid biomarkers for cardiovascular risk prediction in chronic kidney disease: A cross-sectional study.

Chronic kidney disease (CKD) is an important public health issue globally, greatly increasing the prevalence and mortality of cardiovascular disease (...

Combining pathology artificial intelligence and genomic biomarkers to refine long-term postprostatectomy outcome prediction.

BACKGROUND: A multimodal AI (MMAI) model has been validated in prostate biopsy specimens to guide treatment intensification in men receiving radiation...

Screening of diagnostic biomarkers for taurine metabolism-related genes in lupus nephritis and analysis of immune infiltration.

BACKGROUND: Lupus nephritis (LN) represents a serious renal manifestation of systemic lupus erythematosus and is driven by intricate interactions amon...

AI-guided identification of natural CTSL inhibitors with therapeutic potential for renal injury.

Cathepsin L (CTSL) is a prominent therapeutic target for kidney injury, yet clinically available CTSL inhibitors remain limited. Here, we developed an...

Antibody-drug conjugates in selected solid tumours: a position statement update based on findings from the third workshop held by the ETOP IBCSG Partners Foundation.

The European Thoracic Oncology Platform (ETOP) International Breast Cancer Study Group (IBCSG) Partners Foundation initiated a series of workshops for...

Promise and pragmatism of AI in global-scale digital pathology: pan-cancer approaches for clinical practice.

Artificial intelligence (AI) tools for digital pathology have crossed the threshold from pilot project to clinical deployment, with regulatory approva...

Clinical-Radiomics Model Based on T2-Weighted and Diffusion-Weighted Magnetic Resonance Images on Predicting "Double Gray Zone" Prostate Cancer of PSA and PI-RADS.

OBJECTIVES: This study aimed to develop a clinical-radiomics model based on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) to improve...

A Whole-Body PSMA-PET/CT dataset with manually annotated tumor lesions.

We describe a publicly available, large, annotated dataset of 597 whole-body Positron Emission Tomography/Computed Tomography (PET/CT) studies with Pr...

Chatbot Use by Patients Seeking Urogynecologic Consultation: A Randomized Trial.

IMPORTANCE: Urogynecology patients increasingly investigate their problems using technology-based resources, yet the effect of artificial intelligence...

Gut microbiota biomarkers of chronic kidney disease progression identified by 16S rDNA sequencing and machine learning.

Chronic kidney disease (CKD) is a global health concern characterized by high prevalence and mortality rates, yet its underlying pathogenesis remains ...

Anthropometry-adjusted TyG indices predict diabetes, graft failure, and mortality in kidney transplant recipients.

CONTEXT: The triglyceride-glucose (TyG) index is a widely used surrogate marker of insulin resistance and associated with cardiometabolic outcomes. Ho...

Integrating 3D Volumetric Segmentation and LLM-Based Classification for csPCa Detection on mpMRI: Multi-Institutional External Validation.

RATIONALE AND OBJECTIVES: To develop and externally validate integrated models combining three-dimensional (3D) volumetric segmentation and large lang...

MERWACS: Development and external validation of a non-invasive machine learning tool for identifying subjects to be screened for CKD.

Early detection of chronic kidney disease (CKD) is a critical public health priority. However, a gap exists for non-invasive tools to guide screening ...

Using artificial intelligence to identify characteristics associated with clinical and economic outcomes in MASH (FOCUS-MASH).

BACKGROUND: Heterogeneity in the disease characteristics of metabolic dysfunction-associated steatohepatitis (MASH) complicates efforts to identify in...

A machine-learning-derived online prediction model for risk during the activity period in SLE patients: a retrospective historical cross-sectional study.

OBJECTIVE: Given the challenges in predicting systemic lupus erythematosus (SLE) disease activity and the limitations of existing assessment tools, th...

Predicting 3-year mortality after myocardial infarction in a structured care program: A comparative analysis of Cox regression and machine learning models.

BACKGROUND: Accurate risk stratification after myocardial infarction (MI) remains essential for optimizing long-term management. The advantage of mach...

Hierarchies of Smell: Structuring the molecular odor space using Semantic Taxonomies and machine learning.

One of the key challenges to predict odor from molecular structure is unarguably our limited understanding of the odor space and the complexity of the...