Urology

Multimodal data integration using machine learning to predict the risk of clear cell renal cancer metastasis: a retrospective multicentre study.

PURPOSE: To develop and validate a predictive combined model for metastasis in patients with clear c...

CT-based radiomics of machine-learning to screen high-risk individuals with kidney stones.

Screening high-risk populations is crucial for the prevention and treatment of kidney stones. Here, ...

Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images.

BACKGROUND: Metastasis renal cell carcinoma (RCC) patients have extremely high mortality rate. A pre...

Association between machine learning-assisted heavy metal exposures and diabetic kidney disease: a cross-sectional survey and Mendelian randomization analysis.

BACKGROUND AND OBJECTIVE: Heavy metals, ubiquitous in the environment, pose a global public health c...

Artificial INtelligence to Support Informed DEcision-making (INSIDE) for Improved Literature Analysis in Oncology.

BACKGROUND: Defining optimal therapeutic sequencing strategies in prostate cancer (PC) is challengin...

Using machine learning to develop preoperative model for lymph node metastasis in patients with bladder urothelial carcinoma.

BACKGROUND: Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial car...

Machine Learning-Aided Decision-Making Model for the Discontinuation of Continuous Renal Replacement Therapy.

INTRODUCTION: Continuous renal replacement therapy (CRRT) is a primary form of renal support for pat...

Artificial Intelligence Improves the Ability of Physicians to Identify Prostate Cancer Extent.

PURPOSE: Defining prostate cancer contours is a complex task, undermining the efficacy of interventi...

Artificial intelligence for scoring prostate MRI: ready for prospective evaluation.

Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study.

BACKGROUND: Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prost...

DE-AFO: A Robotic Ankle Foot Orthosis for Children with Cerebral Palsy Powered by Dielectric Elastomer Artificial Muscle.

Conventional passive ankle foot orthoses (AFOs) have not seen substantial advances or functional imp...

Contrastive Learning vs. Self-Learning vs. Deformable Data Augmentation in Semantic Segmentation of Medical Images.

To develop a robust segmentation model, encoding the underlying features/structures of the input dat...

Identification of novel biomarkers to distinguish clear cell and non-clear cell renal cell carcinoma using bioinformatics and machine learning.

Renal cell carcinoma (RCC), accounting for 90% of all kidney cancer, is categorized into clear cell ...

Interpretable machine learning identifies metabolites associated with glomerular filtration rate in type 2 diabetes patients.

OBJECTIVE: The co-occurrence of kidney disease in patients with type 2 diabetes (T2D) is a major pub...

ssVERDICT: Self-supervised VERDICT-MRI for enhanced prostate tumor characterization.

PURPOSE: Demonstrating and assessing self-supervised machine-learning fitting of the VERDICT (vascul...

Predicting the Efficacy of Repeated Shockwave Lithotripsy for Treating Patients with Upper Urinary Tract Calculi Using an Artificial Neural Network Model.

PURPOSE: To establish a prediction model for repeated shockwave lithotripsy (SWL) efficacy to help c...

Verification of image quality improvement by deep learning reconstruction to 1.5 T MRI in T2-weighted images of the prostate gland.

This study aimed to evaluate whether the image quality of 1.5 T magnetic resonance imaging (MRI) of ...

Unraveling the genetic and molecular landscape of sepsis and acute kidney injury: A comprehensive GWAS and machine learning approach.

OBJECTIVES: This study aimed to explore the underlying mechanisms of sepsis and acute kidney injury ...

Automatic text classification of prostate cancer malignancy scores in radiology reports using NLP models.

This paper presents the implementation of two automated text classification systems for prostate can...

Predictive approach for liberation from acute dialysis in ICU patients using interpretable machine learning.

Renal recovery following dialysis-requiring acute kidney injury (AKI-D) is a vital clinical outcome ...

Natural language processing pipeline to extract prostate cancer-related information from clinical notes.

OBJECTIVES: To develop an automated pipeline for extracting prostate cancer-related information from...