Urology

Explainable machine learning to predict immunotherapy outcomes in metastatic renal cell carcinoma - Meet-URO 15-AI study.

Metastatic renal cell carcinoma remains clinically challenging because of heterogeneous outcomes and limited predictive biomarkers for immunotherapy. We performed an explainable machine learning analysis using data from the multicenter retrospective Meet-URO 15 study, including 571 patients with metastatic renal cell carcinoma treated with second-line or later nivolumab. Clinical and inflammatory ...

Development and validation of a dual-channel deep learning for continuous acute kidney injury prediction in critically ill patients.

This study aimed to develop and externally validate a real-time, continuous prediction model for 48-h acute kidney injury (AKI) risk in critically ill patients using a dual-channel deep learning model (DC-AKI). The model was developed using electronic health records from 28,099 patients at Beth Israel Deaconess Medical Center and externally validated on two independent cohorts: 3,108 patients from...

Dual-mode analysis of ischemic stroke based on urine SERS spectra and carotid B-ultrasound.

Achieving noninvasive high-frequency monitoring of ischemic stroke (IS) remains a major clinical challenge for timely intervention and precise seconda...

Identification of PRKCB, NLRC4, and TNFSF10 as Key Regulators of the Lipid Metabolism-Autophagy Network in Atherosclerosis.

BACKGROUND: The occurrence and development of atherosclerosis (AS) are closely related to disorders of lipid metabolism and dysfunction of autophagy. ...

Unraveling the adverse outcome pathways of metabolic dysfunction-associated steatotic liver disease triggered by environmental mixtures via biological knowledge-driven machine learning.

Environmental pollutant mixtures are potential risk factors for metabolic dysfunction-associated steatotic liver disease (MASLD), yet their joint effe...

MRI for Prostate Cancer Local Staging: AJR Expert Panel Narrative Review.

The incremental value of multiparametric MRI (mpMRI) in prostate cancer staging has been increasingly recognized, with the accumulated literature indi...

Rapid detection of urinary tract infection by analyzing the dried spots of biological fluids using convolutional neural networks.

To find the cause of infectious diseases such as urinary tract infections, a the diagnostic patterning test was used. In this method, the whole blood ...

Integrative machine learning and CRISPR/Cas9 analysis reveals the role of APOE in lipid metabolism-associated kidney fibrosis.

Kidney fibrosis, characterized by excessive extracellular matrix deposition and progressive renal tissue remodeling, frequently culminates in End-stag...

Insulin resistance surrogate indices and incident cardiovascular disease across cardiovascular-kidney-metabolic stages 0-3: a prospective cohort study.

BACKGROUND: The American Heart Association (AHA) recently proposed the concept of Cardiovascular-Kidney-Metabolic (CKM) syndrome, highlighting the str...

Deep learning-based dose prediction to enhance planning efficiency in cervical brachytherapy with hybrid applicators.

Objective.This study aimed to develop a dose prediction model for hybrid applicators in cervical cancer brachytherapy.Approach.A total of 216 previous...

Developing a machine learning model to predict renal function decline within three years using one-year longitudinal data in patients with type 2 diabetes.

AIMS: The increasing prevalence of type 2 diabetes mellitus (T2DM) has led to an increase in diabetic kidney disease (DKD), which is presently a major...

Nuclear Gradients from Auxiliary-Field Quantum Monte Carlo and Their Applications in ML-Driven Geometry Optimization and Transition State Search.

In this article, we present a method for computing accurate and scalable nuclear forces within the phaseless auxiliary-field quantum Monte Carlo (AFQM...

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered...

An Ultra-Lightweight Cross-scale Attention Mamba Network for Accurate Skin Lesion Segmentation.

Accurate skin lesion segmentation is essential for the early detection and effective management of skin cancer. Existing deep learning architectures a...

Automatic lesion segmentation in ⁶⁸Ga-PSMA PET/CT and ¹⁷⁷Lu-PSMA SPECT/CT: added value of PET-guided SPECT in a bicentric study.

BACKGROUND: Manual segmentation of prostate cancer metastases on PSMA PET/CT and SPECT/CT is time-consuming and poorly scalable, particularly in highl...

Path Planning of Flexible Needle Based on Improved Particle Swarm Optimization Algorithm.

In recent years, flexible needles have garnered significant research attention due to their outstanding steerable flexibility. Path planning of flexib...

Accurate focal-plane selection is crucial for artificial intelligence assessment of three-dimensional urine cytology specimens for bladder cancer screening and surveillance.

BACKGROUND: Bladder cancer is a common and highly recurrent malignancy requiring lifelong surveillance. Urine cytology serves as a noninvasive triage ...

Deep learning-based dose prediction for MR-guided prostate SIB: Supporting rapid feasibility assessment and adaptive editing margin selection.

BACKGROUND: The template-based treatment planning workflow in the Unity magnetic resonance-guided linear accelerator (MR-Linac) helps facilitate the t...

An AI-Driven Multi-Omics Framework Identifies CASP8 as a Clinically Actionable Pyroptosis Biomarker in Bladder Cancer.

Despite rapid advances in multi-omics technologies, translating candidate biomarkers into clinical practice for bladder cancer remains challenging due...

Optimized Prostate Cancer Stage Classification Using XGBoost Based on Racial miRNA Expression.

BACKGROUND/AIM: Prostate cancer has a high mortality rate and shows diagnostic disparities between racial groups, particularly between White and Black...