Urology

Coptidis rhizoma and berberine as anti-cancer drugs: A 10-year updates and future perspectives.

Cancer continues to be among the most substantial health challenges globally. Among various natural ...

Explainable machine learning for predicting lung metastasis of colorectal cancer.

Patients with lung metastasis of colorectal cancer typically have a poor prognosis. Therefore, estab...

FDA-approved artificial intelligence products in abdominal imaging: A comprehensive review.

PURPOSE: This review aims to provide a comprehensive overview of the transformative impact of FDA-ap...

Lipidomic analysis coupled with machine learning identifies unique urinary lipid signatures in patients with interstitial cystitis/bladder pain syndrome.

PURPOSE: To identify biomarkers for diagnosis and classification of interstitial cystitis/bladder pa...

Identification of cancerous tissues based on residual neural network.

The identification of cancerous tissues remains challenging due to the complexity of experimental me...

Machine learning-based characterization of stemness features and construction of a stemness subtype classifier for bladder cancer.

BACKGROUND: Bladder cancer (BLCA) is a highly heterogeneous disease that presents challenges in pred...

Artificial Intelligence Biomarkers Predict Poor Efficacy of Bacillus Calmette-Guérin Rechallenge in Previously Bacillus Calmette-Guérin-Treated Nonmuscle-Invasive Bladder Cancer.

Prior guided deep difference meta-learner for fast adaptation to stylized segmentation.

Radiotherapy treatment planning requires segmenting anatomical structures in various styles, influen...

Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0-3 and the development of a machine learning prediction model: a nationwide prospective cohort study.

BACKGROUND: The American Heart Association recently introduced the concept of cardiovascular-kidney-...

Aptamer-functionalized graphene quantum dots combined with artificial intelligence detect bacteria for urinary tract infections.

OBJECTIVES: Urinary tract infection is one of the most prevalent forms of bacterial infection, and p...

Development and validation of multi-center serum creatinine-based models for noninvasive prediction of kidney fibrosis in chronic kidney disease.

OBJECTIVE: Kidney fibrosis is a key pathological feature in the progression of chronic kidney diseas...

Response to Letter to the Editor: Conformity of ChatGPT Recommendations With the AUA/SUFU Guideline on Postprostatectomy Urinary Incontinence.

Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However,...

Accurate bladder cancer diagnosis using ensemble deep leaning.

There are an estimated 1.3 million cases of cancer globally each year, making it one of the most ser...

Rapid diagnosis of membranous nephropathy based on kidney tissue Raman spectroscopy and deep learning.

Membranous nephropathy (MN) is one of the most common glomerular diseases. Although the diagnostic m...

Prostate Cancer Screening Among Traditionally Underserved Populations at a Large Public Safety-Net Institution.

BACKGROUND: Existing literature underscores racial and sociodemographic disparities in prostate canc...

The Role of Artificial Intelligence in the Evaluation of Prostate Pathology.

Artificial intelligence (AI) is an emerging tool in diagnostic pathology, including prostate patholo...

Integrating machine learning driven virtual screening and molecular dynamics simulations to identify potential inhibitors targeting PARP1 against prostate cancer.

Prostate cancer (PC) is one of the most common types of malignancies in men, with a noteworthy incre...

Comparative study of XGBoost and logistic regression for predicting sarcopenia in postsurgical gastric cancer patients.

The use of machine learning (ML) techniques, particularly XGBoost and logistic regression, to predic...

TET2 gene mutation status associated with poor prognosis of transition zone prostate cancer: a retrospective cohort study based on whole exome sequencing and machine learning models.

BACKGROUND: Prostate cancer (PCa) in the transition zone (TZ) is uncommon and often poses challenges...

External Validation of an Artificial Intelligence Algorithm Using Biparametric MRI and Its Simulated Integration with Conventional PI-RADS for Prostate Cancer Detection.

PURPOSE: Prostate imaging reporting and data systems (PI-RADS) experiences considerable variability ...