Urology

Anoctamin 5 as a protective factor in prostate cancer: Insights from WGCNA, machine learning, and experimental analysis, with a focus on the anoctamin family.

OBJECTIVES: Prostate cancer (PCa) is a prevalent malignancy in males, triggered by multiple factors. This study aimed to identify PCa-specific key genes with clinical significance and clarify their roles in PCa progression. METHODS: To screen PCa-specific key genes, a comprehensive analytical strategy was adopted by integrating weighted gene co-expression network analysis (WGCNA) for mining highly...

Machine Learning Models Using Hospital Admission Characteristics Do Not Optimally Predict Nosocomial Infection Development in a Global Cirrhosis Cohort.

BACKGROUND: Nosocomial infections (NI) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have failed to identify high-risk patients. We aimed to develop machine learning (ML) models to predict NI. METHODS: The CLEARED consortium consists of prospectively enrolled cirrhosis inpatients from >120 centers. Using day-of-admission clinical data, th...

Predicting Bladder Cancer Prognosis by Integrating Multiple Omics Data through an Adversarial Autoencoder-based Cox proportional hazards Network.

Bladder cancer prognosis is a critical factor in determining optimal treatment strategies. However, the heterogeneity of multi-omics data and the high...

Unsupervised Semantic Segmentation Models for Region of Interest Identification.

Spatial omics technologies, such as mass spectrometry imaging (MSI), can capture biomolecular distributions and their spatial locations directly from ...

Emerging multidimensional biomarker system for cardiovascular-kidney-metabolic syndrome: from multi-omics integration to clinical artificial intelligence.

Cardiovascular-kidney-metabolic (CKM) syndrome is an emerging clinical entity that highlights the complex, bidirectional interplay among cardiovascula...

Deep learning-based Wilms tumor segmentation to create 3D models for surgical planning: Implementation in the clinical workflow.

BACKGROUND AND AIM: Creating 3D models based on pre-operative MRI of patients with a Wilms tumor (WT) can aid surgical planning. However, creating the...

Increasing value in the Veterans Affairs Healthcare System (VA) with precision health: a continuing landmark collaboration with the Department of Energy.

OBJECTIVE: Phase II of MVP-CHAMPION, a federal collaboration between the Veterans Affairs Healthcare System (VA) and the Department of Energy (DoE), l...

Using large language models to identify geriatric assessment domains in patients with advanced cancer: A feasibility study.

INTRODUCTION: In older adults with cancer, geriatric assessment (GA) can improve care quality. In-person assessment may not be feasible for all patien...

Machine learning-based prediction of impaired arginine vasopressin secretion during hypertonic saline test.

Hypertonic saline infusion and water deprivation tests are commonly used to stimulate arginine vasopressin (AVP) for the diagnosis of AVP deficiency (...

An explainable clinical-radiomics machine learning model for preoperative prediction of WHO/ISUP nuclear grade in clear cell renal cell carcinoma.

BACKGROUND: Accurate preoperative assessment of the WHO/ISUP nuclear grade of clear cell renal cell carcinoma (ccRCC) is critical for guiding individu...

Combined radiomics, PI-RADS, and clinical model improve significant prostate cancer prediction and guide biopsy decision.

OBJECTIVES: The aim of this study was to develop and validate an MRI radiomics-based predictive model to discriminate significant prostate cancer (sPC...

Urinary Metabolomics and One-Class Classification To Discover Children Affected by Bile Acid Synthetic Disorders: A Case-Study.

Bile acid synthetic disorders (BASDs) are a group of rare metabolic disorders that involve the synthesis of bile acids. Symptoms often overlap with nu...

MMP9 in macrophages: A pivotal biomarker associated with immune dysregulation in interstitial cystitis/bladder pain syndrome.

BACKGROUND: Studies suggest that immune abnormalities play a significant role in the pathophysiology of interstitial cystitis/bladder pain syndrome (I...

Deep learning-based renal artery segmentation and angle estimation for registration of endoscopic images and 3D models in robot-assisted partial nephrectomy.

PURPOSE: Image-guided robot-assisted partial nephrectomy (RAPN) that incorporates three-dimensional (3D) models has improved both oncological and func...

Multidimensional transcriptomic analysis and in vitro experiments dissect the landscape of 2',2',4',4'-Tetrabromodiphenyl ether in bladder cancer progression.

2',2',4',4'-Tetrabromodiphenyl ether (BDE-47), the most widespread congener of polybrominated diphenyl ethers, has attracted considerable attention du...

Artificial Intelligence in Patient Education: ChatGPT for Penile Prosthesis Surgery Counseling, a Likert Scale Analysis.

INTRODUCTION: Erectile dysfunction (ED) significantly impacts quality of life. For patients unresponsive to conservative treatments, penile prosthesis...

Multi-model study of fast VMAT segment dose calculation with deep learning.

OBJECTIVE: Deep learning (DL) methods enable photon dose calculation under two main coordinate representations: Beam's Eye View (BEV) and patient coor...

FedSemiDG: Domain generalized federated semi-supervised medical image segmentation.

Medical image segmentation is challenging due to the diversity of medical images and the lack of labeled data, which motivates recent developments in ...

Integration of AHRR methylation, heavy metals, and clinical characteristics for urothelial carcinoma risk stratification: An explainable artificial intelligence approach.

The short metabolic half-life of conventional tobacco biomarkers often limits their ability to reflect cumulative toxicological damage, which may comp...

Image Quality and Diagnostic Performance of Accelerated T2-weighted Imaging of Prostate with Deep Learning Reconstruction: A Comparative Study.

PURPOSE: To compare accelerated T2-weighted turbo spin-echo imaging with deep learning reconstruction (DLR-TSE) with conventional T2-weighted TSE (con...