Urology

Reply to comment on "Estimating individual risk of catheter-associated urinary tract infections using explainable artificial intelligence on clinical data".

Comment on "Estimating individual risk of catheter-associated urinary tract infections using explainable artificial intelligence on clinical data".

Agreement between Routine-Dose and Lower-Dose CT with and without Deep Learning-based Denoising for Active Surveillance of Solid Small Renal Masses: A Multiobserver Study.

Purpose To assess the agreement between routine-dose (RD) and lower-dose (LD) contrast-enhanced CT s...

Integrative analyses of 16S rDNA sequencing and serum metabolomics demonstrate significant roles for the oral microbiota and serum metabolites in post-kidney transplant diabetes mellitus.

Oral microbiota and serum metabolites play crucial roles in diabetes, but their relationship with po...

Multiclass ensemble framework for enhanced prostate gland Segmentation: Integrating Self-ONN decoders with EfficientNet.

Digital pathology relies on the morphological architecture of prostate glands to recognize cancerous...

Deep learning-based histopathologic segmentation of peritubular capillaries in kidney transplant biopsies.

BACKGROUND: Assessing the extent of inflammation in peritubular capillaries (PTCs) is important for ...

A novel Harris Hawks Optimization-based clustering method for elucidating genetic associations in osteoarthritis and Diverse Cancer Types.

Considering the high incidence of osteoarthritis (OA), especially of the knee and hip, this study ex...

Comparison of three classifiers in detection of obstruction of the lower urinary tract using recorded sounds of voiding.

The aim of this research is to help health care professionals to automatically detect lower urinary ...

Prostate cancer prediction through a hybrid deep learning method applied to histopathological image.

BACKGROUND: Prostate Cancer (PCa) is a severe disease that affects males globally. The Gleason gradi...

Clinical advantages in providing artificial intelligence-assisted prostate cancer diagnosis: A pilot study.

Prostate cancer is a prevalent male malignancy, with increasing incidence rates placing significant ...

Optimizing clinical risk stratification of localized prostate cancer.

PURPOSE OF REVIEW: To review the current risk and prognostic stratification systems in localised pro...

Quantitative CT biomarkers for renal cell carcinoma subtype differentiation: a comparison of DECT, PCT, and CT texture analysis.

OBJECTIVE: To evaluate and compare the diagnostic performance of CT texture analysis (CTTA), perfusi...

MACHINE LEARNING AND BIOINFORMATICS TO IDENTIFY COAGULATION BIOMARKERS IN SEPSIS-RELATED KIDNEY INJURY.

Background: Sepsis-associated acute kidney injury (SA-AKI) is a life-threatening complication with m...

ChatGPT artificial intelligence in clinical data analysis: an example comparing standard fusion prostate biopsy outcomes after robotic-assisted radical prostatectomy (RaRP).

OBJECTIVE: To compare statistical outputs from ChatGPT 4.0 and human experts in both comparative and...

Label-free urinary protein detection through machine learning analysis of single droplet evaporation patterns.

BACKGROUND: Chronic kidney disease (CKD) is a major global public health issue, with a steadily incr...

Artificial intelligence approaches for tumor phenotype stratification from single-cell transcriptomic data.

Single-cell RNA-sequencing (scRNA-seq) coupled with robust computational analysis facilitates the ch...

Validation and Derivation of miRNA-Based Germline Signatures Predicting Radiation Toxicity in Prostate Cancer.

PURPOSE: Although radiotherapy (RT) is one of the primary treatment modalities used in the treatment...

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

This article discusses current research on the detection of urinary cancers using surface-enhanced R...

A Spatial Metabolomics Annotation Workflow Leveraging Cyclic Ion Mobility and Machine Learning-Predicted Collision Cross Sections.

In nontargeted spatial metabolomics, accurate annotation is crucial for understanding metabolites' b...

From planning to prognosis: predicting renal function after minimally-invasive partial nephrectomy with artificial intelligence.

This study presents a machine learning model to predict renal function decline following minimally-i...

Segmentation with artificial intelligence and automated calculation of the corpus callosum index in multiple sclerosis.

OBJECTIVES: To determine the corpus callosum index (CCI) differences between chronic phase multiple ...