Urology

Artificial Intelligence in Reproductive Urology.

PURPOSE OF REVIEW: The promise of artificial intelligence (AI) in medicine has been widely theorized over the past couple of decades. It has only been with technological advances over the past few years that physicians and computer scientists have started discovering its true clinical potential. Reproductive urology is a sub-discipline that AI could be of great contribution, as current predictive ...

Generalizability of A Neural Network Model for Circadian Phase Prediction in Real-World Conditions.

A neural network model was previously developed to predict melatonin rhythms accurately from blue light and skin temperature recordings in individuals on a fixed sleep schedule. This study aimed to test the generalizability of the model to other sleep schedules, including rotating shift work. Ambulatory wrist blue light irradiance and skin temperature data were collected in 16 healthy individuals ...

Validation of a simple equation for glomerular filtration rate measurement based on plasma iohexol disappearance.

BACKGROUND: A simple equation for glomerular filtration rate (GFR) measurement based on only plasma samples during the slow compartment after injectio...

Microwave dielectric property based classification of renal calculi: Application of a kNN algorithm.

The proper management of renal lithiasis presents a challenge, with the recurrence rate of the disease being as high as 46%. To prevent recurrence, th...

An artificial intelligence-based clinical decision support system for large kidney stone treatment.

A decision support system (DSS) was developed to predict postoperative outcome of a kidney stone treatment procedure, particularly percutaneous nephro...

Transoral robotic surgery for hilo-parenchymal submandibular stones: step-by-step description and reasoned approach.

The conservative transoral approach to hilo-parenchymal submandibular stones has been proposed as an alternative to traditional sialadenectomy. The ma...

Reducing the Hausdorff Distance in Medical Image Segmentation With Convolutional Neural Networks.

The Hausdorff Distance (HD) is widely used in evaluating medical image segmentation methods. However, the existing segmentation methods do not attempt...

Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning.

Histopathological images contain morphological markers of disease progression that have diagnostic and predictive values. In this study, we demonstrat...

Fully automated analysis for bone scintigraphy with artificial neural network: usefulness of bone scan index (BSI) in breast cancer.

OBJECTIVE: Artificial neural network (ANN) technology has been developed for clinical use to analyze bone scintigraphy with metastatic bone tumors. It...

Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images.

The goal of this work was to develop a method for accurate and robust automatic segmentation of the prostate clinical target volume in transrectal ult...

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images.

The development of decision support systems for pathology and their deployment in clinical practice have been hindered by the need for large manually ...

Performance of a Natural Language Processing Method to Extract Stone Composition From the Electronic Health Record.

OBJECTIVES: To demonstrate the utility of a natural language processing (NLP) algorithm for mining kidney stone composition in a large-scale electroni...

Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer.

PURPOSE: To develop and validate a robust and accurate registration pipeline for automatic contour propagation for online adaptive Intensity-Modulated...

3D APA-Net: 3D Adversarial Pyramid Anisotropic Convolutional Network for Prostate Segmentation in MR Images.

Accurate and reliable segmentation of the prostate gland using magnetic resonance (MR) imaging has critical importance for the diagnosis and treatment...

Incorporating imaging information from deep neural network layers into image guided radiation therapy (IGRT).

BACKGROUND AND PURPOSE: To investigate a novel markerless prostate localization strategy using a pre-trained deep learning model to interpret routine ...

Machine learning for differentiating metastatic and completely responded sclerotic bone lesion in prostate cancer: a retrospective radiomics study.

OBJECTIVE: Using CT texture analysis and machine learning methods, this study aims to distinguish the lesions imaged via 68Ga-prostate-specific membra...

Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization.

PURPOSE: To develop and validate a classifier system for prediction of prostate cancer (PCa) Gleason score (GS) using radiomics and texture features o...

An integrated model using the Taguchi method and artificial neural network to improve artificial kidney solidification parameters.

BACKGROUND: Hemodialysis mainly relies on the "artificial kidney," which plays a very important role in temporarily or permanently substituting for th...

Fibroblast growth factor 23 and tubular sodium handling in young patients with incipient chronic kidney disease.

BACKGROUND: Experimental studies have shown fibroblast growth factor 23 FGF23)-mediated upregulation of the distal tubule sodium/chloride (NaCl) co-tr...

In-Bore Transrectal MRI-Guided Biopsy With Robotic Assistance in the Diagnosis of Prostate Cancer: An Analysis of 57 Patients.

The objective of our study was to analyze the feasibility and potential role of robotic-assisted transrectal MRI-guided biopsy for the diagnosis of p...