Urology

High spatiotemporal resolution dynamic contrast-enhanced MRI improves the image-based discrimination of histopathology risk groups of peripheral zone prostate cancer: a supervised machine learning approach.

OBJECTIVE: To assess if adding perfusion information from dynamic contrast-enhanced (DCE MRI) acquisition schemes with high spatiotemporal resolution to T2w/DWI sequences as input features for a gradient boosting machine (GBM) machine learning (ML) classifier could better classify prostate cancer (PCa) risk groups than T2w/DWI sequences alone.

Propensity score adjustment using machine learning classification algorithms to control selection bias in online surveys.

Modern survey methods may be subject to non-observable bias, from various sources. Among online surveys, for example, selection bias is prevalent, due to the sampling mechanism commonly used, whereby participants self-select from a subgroup whose characteristics differ from those of the target population. Several techniques have been proposed to tackle this issue. One such is Propensity Score Adju...

Stepwise Description and Outcomes of Bladder Neck Sparing Robot-Assisted Simple Prostatectomy.

To present a stepwise description and outcomes of bladder neck sparing (BNS) robot-assisted simple prostatectomy (RASP). Between March 2015 and Dece...

Error detection using a convolutional neural network with dose difference maps in patient-specific quality assurance for volumetric modulated arc therapy.

The aim of this study was to evaluate the use of dose difference maps with a convolutional neural network (CNN) to detect multi-leaf collimator (MLC) ...

Conventional vs machine learning-based treatment planning in prostate brachytherapy: Results of a Phase I randomized controlled trial.

PURPOSE: The purpose of this study was to evaluate the noninferiority of Day 30 dosimetry between a machine learning-based treatment planning system f...

Re: Andrea Gallioli, Angelo Territo, Romain Boissier, et al. Learning Curve in Robotic-assisted Kidney Transplantation: Results from the European Robotic Urological Society Working Group. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2019.12.008.

Surgical details and renal function change after robot-assisted partial nephrectomy.

OBJECTIVES: To investigate whether differences in surgical details during robot-assisted partial nephrectomy impact postoperative renal function.

Closing the Gap between Prostate Cancer and Deep Learning Detection Tools.

Contemporary Rates and Predictors of Open Conversion During Minimally Invasive Radical Prostatectomy for Nonmetastatic Prostate Cancer.

To test contemporary rates and predictors of open conversion at minimally invasive (laparoscopic or robotic) radical prostatectomy (MIRP). Within th...

MEDICASCY: A Machine Learning Approach for Predicting Small-Molecule Drug Side Effects, Indications, Efficacy, and Modes of Action.

To improve the drug discovery yield, a method which is implemented at the beginning of drug discovery that accurately predicts drug side effects, indi...

A comparative study of machine learning and deep learning algorithms to classify cancer types based on microarray gene expression data.

Cancer classification is a topic of major interest in medicine since it allows accurate and efficient diagnosis and facilitates a successful outcome i...

Risk of hernia formation after radical prostatectomy: a comparison between open and robot-assisted laparoscopic radical prostatectomy within the prospectively controlled LAPPRO trial.

PURPOSE: In addition to incisional hernia, inguinal hernia is a recognized complication to radical retropubic prostatectomy. To compare the risk of de...

Reply to Jinna Yao, Henry C.C. Pleass, and Howard M.H. Lau's Letter to the Editor re: Andrea Gallioli, Angelo Territo, Romain Boissier, et al. Learning Curve in Robot-assisted Kidney Transplantation: Results from the European Robotic Urological Society Working Group. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2019.12.008.

Automated Detection and Grading of Non-Muscle-Invasive Urothelial Cell Carcinoma of the Bladder.

Accurate grading of non-muscle-invasive urothelial cell carcinoma is of major importance; however, high interobserver variability exists. A fully auto...

Machine learning application for incident prostate adenocarcinomas automatic registration in a French regional cancer registry.

UNLABELLED: Cancer registries are collections of curated data about malignant tumor diseases. The amount of data processed by cancer registries increa...

Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images.

PURPOSE: Needle-based procedures for diagnosing and treating prostate cancer, such as biopsy and brachytherapy, have incorporated three-dimensional (3...

DeepDose: Towards a fast dose calculation engine for radiation therapy using deep learning.

We present DeepDose, a deep learning framework for fast dose calculations in radiation therapy. Given a patient anatomy and linear-accelerator IMRT mu...

Role of Artificial Intelligence in Kidney Disease.

Artificial intelligence (AI), as an advanced science technology, has been widely used in medical fields to promote medical development, mainly applied...

Comment on "Deep learning computer vision algorithm for detecting kidney stone composition".

Machine learning, the kidney, and genotype-phenotype analysis.

With biomedical research transitioning into data-rich science, machine learning provides a powerful toolkit for extracting knowledge from large-scale ...