Urology

Physics-informed machine learning digital twin for reconstructing prostate cancer tumor growth via PSA tests.

Existing prostate cancer monitoring methods, reliant on prostate-specific antigen (PSA) measurements...

Evaluating the efficacy of using large language models in preoperative prediction of microvascular invasion in HCC: a multicenter study.

Primary liver cancer is the sixth most commonly diagnosed cancer globally and the third leading caus...

Cardiovascular Indexes and Oxidative Balance in Advanced Cardiovascular-Kidney-Metabolic Syndrome.

OBJECTIVE: The cardiovascular-kidney-metabolic (CKM) syndrome lacks clear strategies for risk reduct...

Implicit versus explicit Bayesian priors for epistemic uncertainty estimation in clinical decision support.

Deep learning models offer transformative potential for personalized medicine by providing automated...

Unveiling key pathomic features for automated diagnosis and Gleason grade estimation in prostate cancer.

BACKGROUND: Recent advances in histology scanning technology and Artificial Intelligence (AI) offer ...

Machine learning-based MRI imaging for prostate cancer diagnosis: systematic review and meta-analysis.

OBJECTIVE: This study aims to evaluate the diagnostic value of machine learning-based MRI imaging in...

Transferring Knowledge from MM to QM: A Graph Neural Network-Based Implicit Solvent Model for Small Organic Molecules.

The conformational ensemble of a molecule is strongly influenced by the surrounding environment. Cor...

Machine learning and transcriptomics in the research on biomarkers of chronic kidney disease: technical robustness, clinical feasibility and ethical standards.

Finding the original mass: A machine learning model and its deployment for lithic scrapers.

Predicting the original mass of a retouched scraper has long been a major goal in lithic analysis. I...

A visualized machine learning model using noninvasive parameters to differentiate men with and without prostatic carcinoma before biopsy.

This study aimed to create a visualized extreme gradient boosting (XGBOOST) model to distinguish pro...

The 31st Annual Prostate Cancer Foundation Scientific Retreat Report.

BACKGROUND: The 31st Annual Prostate Cancer Foundation (PCF) Scientific Retreat took place in Carlsb...

Comments on "deep learning for kidney trauma detection: CT image algorithm performance and external validation. - experimental study".

Preparing clinical research data for artificial intelligence readiness: insights from the National Institute of Diabetes and Digestive and Kidney Diseases data centric challenge.

OBJECTIVES: The success of artificial intelligence (AI) and machine learning (ML) approaches in biom...

ASO Visual Abstract: Artificial Intelligence-Assisted Segmentation of Prostate Tumors and Neurovascular Bundles: Applications in Precision Surgery for Prostate Cancer.

Automated radiotherapy treatment planning guided by GPT-4Vision.

. Radiotherapy treatment planning is a time-consuming and potentially subjective process that requir...

Clinical diagnostic and prognostic value of homocysteine combined with hemoglobin [f (Hcy-Hb)] in cardio-renal syndrome caused by primary acute myocardial infarction.

BACKGROUND: Cardio-renal syndrome (CRS), characterized by multi-organ interaction, is frequently ove...

Development and validation of risk prediction models for acute kidney disease in gout patients: a retrospective study using machine learning.

BACKGROUND: Limited research has been conducted on the prevalence of acute kidney injury (AKI) and a...

Comment on "Artificial Intelligence-based multi-modal prediction for nuclear grading status and prognosis of clear cell renal cell carcinoma: a multicenter cohort study".

Advanced feature engineering in Acute:Chronic Workload Ratio (ACWR) calculation for injury forecasting in elite soccer.

Controlling training monotony and monitoring external workload using the Acute:Chronic Workload Rati...

Developing an artificial intelligence model for phase recognition in robot-assisted radical prostatectomy.

OBJECTIVES: To develop and evaluate a convolutional neural network (CNN)-based model for recognising...

Artificial intelligence-generated apparent diffusion coefficient (AI-ADC) maps for prostate gland assessment: a multi-reader study.

OBJECTIVE: To compare the quality of AI-ADC maps and standard ADC maps in a multi-reader study.