Urology

Noninvasive identification of HER2 status by integrating multiparametric MRI-based radiomics model with the vesical imaging-reporting and data system (VI-RADS) score in bladder urothelial carcinoma.

PURPOSE: HER2 expression is crucial for the application of HER2-targeted antibody-drug conjugates. This study aims to construct a predictive model by integrating multiparametric magnetic resonance imaging (mpMRI) based multimodal radiomics and the Vesical Imaging-Reporting and Data System (VI-RADS) score for noninvasive identification of HER2 status in bladder urothelial carcinoma (BUC).

Interpretable CT Radiomics-based Machine Learning Model for Preoperative Prediction of Ki-67 Expression in Clear Cell Renal Cell Carcinoma.

RATIONALE AND OBJECTIVES: To develop and externally validate interpretable CT radiomics-based machine learning (ML) models for preoperative Ki-67 expression prediction in clear cell renal cell carcinoma (ccRCC).

Harnessing NLP to investigate biomarker interactions and CVD risks in elderly chronic kidney disease patients.

Chronic kidney disease (CKD) significantly increases the risk of CVD diseases, particularly among elderly patients. Understanding the interaction betw...

Assessing the Effectiveness of Interactive Robot-Assisted Virtual Health Coaching for Health Literacy and Disease Knowledge of Patients with Chronic Kidney Disease: Quasiexperimental Study.

BACKGROUND: Chronic kidney disease (CKD) imposes a significant global health and economic burden, impacting millions globally. Despite its high preval...

Using XBGoost, an interpretable machine learning model, for diagnosing prostate cancer in patients with PSA < 20 ng/ml based on the PSAMR indicator.

To create a diagnostic tool before biopsy for patients with prostate-specific antigen (PSA) levels < 20 ng/ml to minimize prostate biopsy-related disc...

Prediction of urinary tract infection using machine learning methods: a study for finding the most-informative variables.

BACKGROUND: Urinary tract infection (UTI) is a frequent health-threatening condition. Early reliable diagnosis of UTI helps to prevent misuse or overu...

The effect of renal function on the clinical outcomes and management of patients hospitalized with hyperglycemic crises.

BACKGROUND: The global prevalence of diabetes has been rising rapidly in recent years, leading to an increase in patients experiencing hyperglycemic c...

CT-Based Body Composition Measures and Systemic Disease: A Population-Level Analysis Using Artificial Intelligence Tools in Over 100,000 Patients.

CT-based abdominal body composition measures have shown associations with important health outcomes. Advances in artificial intelligence (AI) now all...

The role of endothelial cell-related gene COL1A1 in prostate cancer diagnosis and immunotherapy: insights from machine learning and single-cell analysis.

BACKGROUND: Endothelial cells are integral components of the tumor microenvironment and play a multifaceted role in tumor immunotherapy. Targeting end...

Multi-Scale Pyramid Squeeze Attention Similarity Optimization Classification Neural Network for ERP Detection.

Event-related potentials (ERPs) can reveal brain activity elicited by external stimuli. Innovative methods to decode ERPs could enhance the accuracy o...

Revolutionizing surgery: AI and robotics for precision, risk reduction, and innovation.

Artificial intelligence and robotics are revolutionizing surgical practices by enhancing precision, efficiency, and patient outcomes. With global heal...

AI predicting recurrence in non-muscle-invasive bladder cancer: systematic review with study strengths and weaknesses.

BACKGROUND: Non-muscle-invasive Bladder Cancer (NMIBC) is notorious for its high recurrence rate of 70-80%, imposing a significant human burden and ma...

Differential Diagnosis of Urinary Cancers by Surface-Enhanced Raman Spectroscopy and Machine Learning.

Bladder, kidney, and prostate cancers are prevalent urinary cancers, and developing efficient detection methods is of significance for the early diagn...

Intelligence analysis of drug nanoparticles delivery efficiency to cancer tumor sites using machine learning models.

This study focuses on the use of machine learning (ML) models to predict the biodistribution of nanoparticles in various organs, using a dataset deriv...

Urine kidney injury molecule-1 predicts subclinical kidney disease among persons living with HIV initiating tenofovir disoproxil fumarate-based ART in Zambia.

INTRODUCTION: Antiretroviral therapy (ART) increases the life expectancy of persons living with HIV (PLWH), but not without potentially serious advers...

mCNN-glucose: Identifying families of glucose transporters using a deep convolutional neural network based on multiple-scanning windows.

Glucose transporters are essential carrier proteins that function on the phospholipid bilayer to facilitate glucose diffusion across cell membranes. T...

Preoperative prediction of the selection of the NOTES approach for patients with symptomatic simple renal cysts via an interpretable machine learning model: a retrospective study of 264 patients.

BACKGROUND: There are multiple surgical approaches for treating symptomatic simple renal cysts (SSRCs). The natural orifice transluminal endoscopic su...

Unsupervised self-organising map classification of Raman spectra from prostate cell lines uncovers substratified prostate cancer disease states.

Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressiv...

Machine learning-based interpretation of non-contrast feature tracking strain analysis and T1/T2 mapping for assessing myocardial viability.

Assessing myocardial viability is crucial for managing ischemic heart disease. While late gadolinium enhancement (LGE) cardiovascular magnetic resonan...

Predicting intermediate-risk prostate cancer using machine learning.

PURPOSES: Intermediate-risk prostate cancer (IR PCa) is the most common risk group for localized prostate cancer. This study aimed to develop a machin...