Urology

Prostate Cancer Nodal Staging: Using Deep Learning to Predict Ga-PSMA-Positivity from CT Imaging Alone.

Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT can be performed, although cost remains high and availability is limited. Therefore, computed tomography (CT) continues to be the most used modality for PCa staging. We assessed if convolutional neural networks (CNNs) can be trained to determine 68Ga-PSMA-PET/CT-lymph node status from CT alone. In 5...

Robot-assisted laparoscopic pyelotomy and ileal ureter substitution: video demonstration.

Comparison of statistical machine learning models for rectal protocol compliance in prostate external beam radiation therapy.

PURPOSE: Limiting the dose to the rectum can be one of the most challenging aspects of creating a dosimetric external beam radiation therapy (EBRT) pl...

Same-day discharge surgery for robot-assisted radical prostatectomy in the era of ERAS and prehabilitation pathways: a contemporary, comparative, feasibility study.

PURPOSE: To assess the feasibility of same-day discharge (SDD) after robot-assisted radical prostatectomy (RARP) in the context of enhanced recovery a...

MS-Net: Multi-Site Network for Improving Prostate Segmentation With Heterogeneous MRI Data.

Automated prostate segmentation in MRI is highly demanded for computer-assisted diagnosis. Recently, a variety of deep learning methods have achieved ...

An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy.

We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing,...

Machine Learning and Bioinformatics Models to Identify Pathways that Mediate Influences of Welding Fumes on Cancer Progression.

Welding generates and releases fumes that are hazardous to human health. Welding fumes (WFs) are a complex mix of metallic oxides, fluorides and silic...

PTML Model of ChEMBL Compounds Assays for Vitamin Derivatives.

Determining the biological activity of vitamin derivatives is needed given that organic synthesis of analogs of vitamins is an active field of interes...

Cellular and Molecular Probing of Intact Human Organs.

Optical tissue transparency permits scalable cellular and molecular investigation of complex tissues in 3D. Adult human organs are particularly challe...

Generalizing Deep Learning for Medical Image Segmentation to Unseen Domains via Deep Stacked Transformation.

Recent advances in deep learning for medical image segmentation demonstrate expert-level accuracy. However, application of these models in clinically ...

Prospective evaluation of visual function in patients with ocular diseases after robot-assisted laparoscopic prostatectomy.

OBJECTIVES: To investigate intraocular pressure and visual function in patients with ocular diseases undergoing robot-assisted laparoscopic prostatect...

Ga-PSMA PET/CT versus CT and bone scan for investigation of PSA failure post radical prostatectomy.

OBJECTIVE: To evaluate the use of Gallium-68 prostate-specific membrane antigen positron emission tomography/computed tomography (Ga-PSMA PET/CT), com...

Automated differentiation of benign renal oncocytoma and chromophobe renal cell carcinoma on computed tomography using deep learning.

OBJECTIVES: To develop and evaluate the feasibility of an objective method using artificial intelligence (AI) and image processing in a semi-automated...

Comparison Studies of "Ultrathin Parenchyma" Resection and Sharp Dissection in Robotic Partial Nephrectomy for Renal Tumors.

The aim of this study was to introduce the "ultrathin parenchyma" resection in a robot-assisted partial nephrectomy (RAPN) via the retroperitoneal ap...

Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.

BACKGROUND: Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Fai...

RefDNN: a reference drug based neural network for more accurate prediction of anticancer drug resistance.

Cancer is one of the most difficult diseases to treat owing to the drug resistance of tumour cells. Recent studies have revealed that drug responses a...

Machine learning for syndromic surveillance using veterinary necropsy reports.

The use of natural language data for animal population surveillance represents a valuable opportunity to gather information about potential disease ou...

Deep DoseNet: a deep neural network for accurate dosimetric transformation between different spatial resolutions and/or different dose calculation algorithms for precision radiation therapy.

The purpose of this work is to introduce a novel deep learning strategy to obtain highly accurate dose plan by transforming from a dose distribution c...

A Three-Gene Classifier Associated With MicroRNA-Mediated Regulation Predicts Prostate Cancer Recurrence After Radical Prostatectomy.

BACKGROUND AND OBJECTIVE: After radical prostatectomy (RP), prostate cancer (PCa) patients may experience biochemical recurrence (BCR) and clinical re...

An artificial neural network to model response of a radiotherapy beam monitoring system.

PURPOSE: The integral quality monitor (IQM) is a real-time radiotherapy beam monitoring system, which consists of a spatially sensitive large-area ion...