Urology

A Tri-Stage Wrapper-Filter Feature Selection Framework for Disease Classification.

In machine learning and data science, feature selection is considered as a crucial step of data preprocessing. When we directly apply the raw data for classification or clustering purposes, sometimes we observe that the learning algorithms do not perform well. One possible reason for this is the presence of redundant, noisy, and non-informative features or attributes in the datasets. Hence, featur...

The Growing Role for Semantic Segmentation in Urology.

As the quantity and quality of cross-sectional imaging data increase, it is important to be able to make efficient use of the information. Semantic segmentation is an emerging technology that promises to improve the speed, reproducibility, and accuracy of analysis of medical imaging, and to allow visualization methods that were previously impossible. Manual image segmentation often requires expert...

An Audit of Robot-Assisted Minimally Invasive Surgeries in Children: Early Experience from a Tertiary Care Center in India.

Over the last decade, a significant rise in pediatric robot-assisted minimally invasive surgeries has been observed. Apart from the urological surger...

Identification of novel biomarkers in Hunner's interstitial cystitis using the CIBERSORT, an algorithm based on machine learning.

BACKGROUND:  Hunner's interstitial cystitis (HIC) is a complex disorder characterized by pelvic pain, disrupted urine storage, and Hunner lesions seen...

Ropinirole involved in a fatal case: blood and urinary concentrations.

PURPOSE: Ropinirole is an antiparkinsonian  drug and has recently been suggested to be effective in amyotrophic lateral sclerosis. It is expected that...

Wide & Deep neural network model for patch aggregation in CNN-based prostate cancer detection systems.

Prostate cancer (PCa) is one of the most commonly diagnosed cancer and one of the leading causes of death among men, with almost 1.41 million new case...

Intracorporeal Versus Extracorporeal Robot-assisted Kidney Autotransplantation: Experience of the ERUS RAKT Working Group.

BACKGROUND: Kidney autotransplantation is a useful technique to be reserved for cases in which kidney function is compromised by a complex anatomical ...

Deep learning-based transformation of H&E stained tissues into special stains.

Pathology is practiced by visual inspection of histochemically stained tissue slides. While the hematoxylin and eosin (H&E) stain is most commonly use...

Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps.

Diagnosis and Gleason grading of prostate cancer in biopsies are critical for the clinical management of men with prostate cancer. Despite this, the h...

Clinical implementation of deep-learning based auto-contouring tools-Experience of three French radiotherapy centers.

Deep-learning (DL)-based auto-contouring solutions have recently been proposed as a convincing alternative to decrease workload of target volumes and ...

Retrospective Concomitant Nonrandomized Comparison of "Touch" Cautery Versus Athermal Dissection of the Prostatic Vascular Pedicles and Neurovascular Bundles During Robot-assisted Radical Prostatectomy.

BACKGROUND: During robotic-assisted radical prostatectomy (RARP), the use of electrocautery near the neurovascular bundles (NVBs) frequently results i...

Machine learning model for early prediction of acute kidney injury (AKI) in pediatric critical care.

BACKGROUND: Acute kidney injury (AKI) in pediatric critical care patients is diagnosed using elevated serum creatinine, which occurs only after kidney...

Incremental modification of robotic prostatectomy technique can lead to aggregated marginal gains to significantly improve functional outcomes without compromising oncological control.

INTRODUCTION AND OBJECTIVES: Surgeons should aim for continuous quality improvement. The aim of this study was to evaluate the impact of incremental c...

Chronic kidney disease diagnosis using decision tree algorithms.

BACKGROUND: Chronic Kidney Disease (CKD), i.e., gradual decrease in the renal function spanning over a duration of several months to years without any...

Diagnostic performance of deep learning models for detecting bone metastasis on whole-body bone scan in prostate cancer.

PURPOSE: We evaluated the performance of deep learning classifiers for bone scans of prostate cancer patients.

Intraoperative multimodal analgesic bundle containing dexmedetomidine and ketorolac may improve analgesia after robot-assisted prostatectomy in patients receiving rectus sheath blocks.

BACKGROUND: Minimally invasive robot-assisted laparoscopic radical prostatectomy (RALP) has replaced open prostatectomy. However, RALP does not reduce...

Resolution-based distillation for efficient histology image classification.

Developing deep learning models to analyze histology images has been computationally challenging, as the massive size of the images causes excessive s...

Robot-Assisted Laparoscopic Retroperitoneal Renal Artery Aneurysm Repair: A Rare Case Report and Literature Review.

INTRODUCTION: The treatment of renal artery aneurysms (RAAs) includes surgical repair and endovascular techniques. Surgical repair is divided into ope...

[Digital transformation in urology-opportunity, risk or necessity?].

Ultimately, new (digital) techniques and artificial intelligence (AI) applications are changing the working environment in urology. This can be an opp...

Detection and PI-RADS classification of focal lesions in prostate MRI: Performance comparison between a deep learning-based algorithm (DLA) and radiologists with various levels of experience.

PURPOSE: To compare the performance of lesion detection and Prostate Imaging-Reporting and Data System (PI-RADS) classification between a deep learnin...