Urology

Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis.

OBJECTIVES: The aim of this study was to systematically review the literature and perform a meta-ana...

Bioinformatics analysis of the genes involved in the extension of prostate cancer to adjacent lymph nodes by supervised and unsupervised machine learning methods: The role of SPAG1 and PLEKHF2.

The present study aimed to identify the genes associated with the involvement of adjunct lymph nodes...

Synthesis Success Calculator: Predicting the Rapid Synthesis of DNA Fragments with Machine Learning.

The synthesis and assembly of long DNA fragments has greatly accelerated synthetic biology and biote...

Study on Urinary Candidate Metabolome for the Early Detection of Breast Cancer.

A metabolomic study for determination of certain urinary metabolomes, 1-methyladenosine (1-MA), 1-me...

Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy.

PURPOSE: Auto-contouring may reduce workload, interobserver variation, and time associated with manu...

Using decision curve analysis to benchmark performance of a magnetic resonance imaging-based deep learning model for prostate cancer risk assessment.

OBJECTIVES: To benchmark the performance of a calibrated 3D convolutional neural network (CNN) appli...

Re: Artificial Intelligence for Diagnosis and Grading of Prostate Cancer in Biopsies: A Population-Based, Diagnostic Study.

Label-driven magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) registration using weakly supervised learning for MRI-guided prostate radiotherapy.

Registration and fusion of magnetic resonance imaging (MRI) and transrectal ultrasound (TRUS) of the...

Development of robust artificial neural networks for prediction of 5-year survival in bladder cancer.

PURPOSE: When exploring survival outcomes for patients with bladder cancer, most studies rely on con...

Simplified PADUA Renal (SPARE) Nephrometry Scoring System: External Validation, Interobserver Variability, and Comparison with RENAL and PADUA in a Single-center Robotic Partial Nephrectomy Series.

BACKGROUND: The RENAL (radius [R], exophytic/endophytic [E], nearness to collecting system/sinus [N]...

On-clamp versus purely off-clamp robot-assisted partial nephrectomy in solitary kidneys: comparison of perioperative outcomes and chronic kidney disease progression at two high-volume centers.

BACKGROUND: Minimal literature describes the impact of hilar control on the progression to chronic k...

Analyzing National Incidences and Predictors of Open Conversion During Minimally Invasive Partial Nephrectomy for cT1 Renal Masses.

To analyze predictors of open conversion during minimally invasive partial nephrectomy (MIPN) for c...

Automatic segmentation of pelvic organs-at-risk using a fusion network model based on limited training samples.

Efficient and accurate methods are needed to automatically segmenting organs-at-risk (OAR) to accel...

Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.

Automatic and reliable prostate segmentation is an essential prerequisite for assisting the diagnosi...

Boosting radiotherapy dose calculation accuracy with deep learning.

In radiotherapy, a trade-off exists between computational workload/speed and dose calculation accura...

Exploring the mechanism of TCM formulae in the treatment of different types of coronary heart disease by network pharmacology and machining learning.

Traditional Chinese medicine (TCM) has long been used in the clinical treatment of coronary heart di...

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis.

Glomerular cell death is a pathological feature of myeloperoxidase anti neutrophil cytoplasmic antib...

Histologic tissue components provide major cues for machine learning-based prostate cancer detection and grading on prostatectomy specimens.

Automatically detecting and grading cancerous regions on radical prostatectomy (RP) sections facilit...

Deep learning detection of prostate cancer recurrence with F-FACBC (fluciclovine, Axumin®) positron emission tomography.

PURPOSE: To evaluate the performance of deep learning (DL) classifiers in discriminating normal and ...

First robot-assisted radical prostatectomy in a client-owned Bernese mountain dog with prostatic adenocarcinoma.

OBJECTIVE: To describe robot-assisted radical prostatectomy (RARP) and report the short-term outcome...

Editorial for "Deep-Learning-Based Artificial Intelligence for PI-RADS Classification to Assist Multiparametric Prostate MRI Interpretation: A Development Study".