Urology

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

BACKGROUND: Existing literature underscores racial and sociodemographic disparities in prostate cancer screening (PCS) in the USA.

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

Artificial intelligence (AI) is an emerging tool in diagnostic pathology, including prostate pathology. This review summarizes the possibilities offered by AI and also discusses the challenges and risks. AI has the potential to assist in the diagnosis and grading of prostate cancer. Diagnostic safety can be enhanced by avoiding the accidental underdiagnosis of small lesions. Another possible benef...

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 increase in newly diagnosed cases in recent years. PARP...

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 predict sarcopenia among postsurgical gastric cancer pat...

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 for early diagnosis, but its genomic determinants...

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 in inter-reader performance. Artificial Intelligen...

Using machine learning to investigate the influence of the prenatal chemical exposome on neurodevelopment of young children.

Research investigating the prenatal chemical exposome and child neurodevelopment has typically focused on a limited number of chemical exposures and c...

Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification.

To address the public health issue of renal failure and the global shortage of nephrologists, an AI-based system has been developed to automatically i...

Interpretable Machine Learning Radiomics Model Predicts 5-year Recurrence-Free Survival in Non-metastatic Clear Cell Renal Cell Carcinoma: A Multicenter and Retrospective Cohort Study.

RATIONALE AND OBJECTIVES: To develop and validate a computed tomography (CT) radiomics-based interpretable machine learning (ML) model for predicting ...

Development of machine learning models to predict the risk of fungal infection following flexible ureteroscopy lithotripsy.

BACKGROUND: The flexible ureteroscopy lithotripsy (F-URL) is an important treatment for upper urinary tract stones. However, urolithiasis, surgical pr...

A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation.

BACKGROUND: Postoperative acute kidney injury (AKI) is a significant risk associated with surgeries under general anesthesia, often leading to increas...

A comparison of neural networks and regression-based approaches for estimating kidney function in pediatric chronic kidney disease: Practical predictive epidemiology for clinical management of a progressive disease.

PURPOSE: Clinical management of pediatric chronic kidney disease requires estimation of glomerular filtration rate (eGFR). Currently, eGFR is determin...

Risk prediction for acute kidney disease and adverse outcomes in patients with chronic obstructive pulmonary disease: an interpretable machine learning approach.

BACKGROUND: Little is known about acute kidney injury (AKI) and acute kidney disease (AKD) in patients with chronic obstructive pulmonary disease (COP...

Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus.

BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetic mellitus (DM). More sensitive methods for early DKD predict...

[Making prostate cancer research accessible: chatGPT-4 as a tool to enhance lay communication].

BACKGROUND AND OBJECTIVE: The abundant potential arising from various applications of artificial intelligence is gradually influencing academic and sc...

Development and Validation of an Algorithm for Segmentation of the Prostate and its Zones from Three-dimensional Transrectal Multiparametric Ultrasound Images.

BACKGROUND AND OBJECTIVE: Multiparametric ultrasound (mpUS) is being investigated as an alternative to magnetic resonance imaging (MRI) for detection ...

Development and validation of interpretable machine learning models to predict distant metastasis and prognosis of muscle-invasive bladder cancer patients.

Muscle-Invasive Bladder Cancer (MIBC) is a more aggressive disease than non-muscle-invasive bladder cancer (NMIBC), with greater chances of metastasis...

Brain tumor segmentation and detection in MRI using convolutional neural networks and VGG16.

BackgroundIn this research, we explore the application of Convolutional Neural Networks (CNNs) for the development of an automated cancer detection sy...

Effects of Renal Function on the Multimodal Brain Networks Affecting Mild Cognitive Impairment Converters in End-Stage Renal Disease.

RATIONALE AND OBJECTIVES: Cognitive decline is common in End-Stage Renal Disease (ESRD) patients, yet its neural mechanisms are poorly understood. Thi...

Root of Prunus persica (taoshugen) ameliorated renal fibrosis by inhibiting TGF-β signaling via upregulating Pmepa1 in mice with unilateral ureter obstruction.

ETHNOPHARMACOLOGICAL RELEVANCE: Various parts of Prunus persica (L.) Batsch (peach) exhibit medicinal properties and are utilized in traditional Chine...