Urology

Avoiding Urinary Catheterization in Patients Undergoing Atrial Fibrillation Catheter Ablation.

PURPOSE: Indwelling urinary catheters are commonly inserted when administering general anesthesia. H...

Predicting breast cancer risk using personal health data and machine learning models.

Among women, breast cancer is a leading cause of death. Breast cancer risk predictions can inform sc...

Technical Note: A feasibility study on deep learning-based radiotherapy dose calculation.

PURPOSE: Various dose calculation algorithms are available for radiation therapy for cancer patients...

Discontinuation of Proton Pump Inhibitors in Patients With Chronic Kidney Disease.

Proton pump inhibitors (PPIs) are commonly used medications and are historically well tolerated. Re...

Deep learning of diffraction image patterns for accurate classification of five cell types.

Development of label-free methods for accurate classification of cells with high throughput can yiel...

Commentary: Automated Diagnosis and Gleason Grading of Prostate Cancer - Are Artificial Intelligence Systems Ready for Prime Time?

Automatic cancer tissue detection using multispectral photoacoustic imaging.

PURPOSE: In the case of multispecimen study to locate cancer regions, such as in thyroidectomy and p...

Predicting material properties by integrating high-throughput experiments, high-throughput ab-initio calculations, and machine learning.

High-throughput experiments (HTEs) have been powerful tools to obtain many materials data. However, ...

Prostate Cancer Detection using Deep Convolutional Neural Networks.

Prostate cancer is one of the most common forms of cancer and the third leading cause of cancer deat...

Endoscopic-assisted robotic pyelolithotomy: a viable treatment option for complex pediatric nephrolithiasis.

INTRODUCTION AND OBJECTIVE: Endourological and percutaneous approaches are the standard of care for ...

An Effective MR-Guided CT Network Training for Segmenting Prostate in CT Images.

Segmentation of prostate in medical imaging data (e.g., CT, MRI, TRUS) is often considered as a crit...

Artificial intelligence and neural networks in urology: current clinical applications.

INTRODUCTION: As we enter the era of "big data," an increasing amount of complex health-care data wi...

A continual prediction model for inpatient acute kidney injury.

Acute kidney injury (AKI) commonly occurs in hospitalized patients and can lead to serious medical c...

Deep learning and taphonomy: high accuracy in the classification of cut marks made on fleshed and defleshed bones using convolutional neural networks.

Accurate identification of bone surface modifications (BSM) is crucial for the taphonomic understand...

A comparison between two semantic deep learning frameworks for the autosomal dominant polycystic kidney disease segmentation based on magnetic resonance images.

BACKGROUND: The automatic segmentation of kidneys in medical images is not a trivial task when the s...

Identification of aberrantly methylated‑differentially expressed genes and gene ontology in prostate cancer.

Prostate cancer (PCa) is the most frequent urological malignancy in men worldwide. DNA methylation h...

Comparison of Initial Experience with Transrectal Magnetic Resonance Imaging Cognitive Guided Micro-Ultrasound Biopsies versus Established Transperineal Robotic Ultrasound Magnetic Resonance Imaging Fusion Biopsies for Prostate Cancer.

PURPOSE: We compared cancer detection rates in patients who underwent magnetic resonance imaging cog...

A multicolor multiplex lateral flow assay for high-sensitivity analyte detection using persistent luminescent nanophosphors.

Incorporating two persistent luminescent nanophosphors (PLNPs), green-emitting SrAlO:Eu,Dy (SAO) and...

Identifying bladder rupture following traumatic pelvic fracture: A machine learning approach.

INTRODUCTION: Bladder rupture following blunt pelvic trauma is rare though can have significant sequ...

Evaluation of complexity and deliverability of prostate cancer treatment plans designed with a knowledge-based VMAT planning technique.

PURPOSE: Knowledge-based planning (KBP) techniques have been reported to improve plan quality, effic...

Pulse Wave Velocity and Machine Learning to Predict Cardiovascular Outcomes in Prediabetic and Diabetic Populations.

Few studies have addressed the predictive value of arterial stiffness determined by pulse wave veloc...