AIMC Topic: Humans

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Open data and injuries in urban areas-A spatial analytical framework of Toronto using machine learning and spatial regressions.

PloS one
Injuries have become devastating and often under-recognized public health concerns. In Canada, injuries are the leading cause of potential years of life lost before the age of 65. The geographical patterns of injury, however, are evident both over sp...

Comparison of Patient-reported Health-related Quality of Life Between Open Radical Cystectomy and Robot-assisted Radical Cystectomy with Intracorporeal Urinary Diversion: Interim Analysis of a Randomised Controlled Trial.

European urology focus
BACKGROUND: Open radical cystectomy (ORC) is still considered the reference approach for RC, although robot-assisted RC (RARC) has recently gained in popularity. There are literature reports on perioperative and oncologic outcomes of RARC, but functi...

Liver Fat Assessment in Multiview Sonography Using Transfer Learning With Convolutional Neural Networks.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: To develop and evaluate deep learning models devised for liver fat assessment based on ultrasound (US) images acquired from four different liver views: transverse plane (hepatic veins at the confluence with the inferior vena cava, right p...

The ameliorating approach of nanorobotics in the novel drug delivery systems: a mechanistic review.

Journal of drug targeting
Nanoscale robotics have the ability that it can productively transform multiple energy sources into motion and strength which reflects an expeditiously appearing and captivating area for research of robotics. In today's plethora, biomedical nanorobot...

Finding event structure in time: What recurrent neural networks can tell us about event structure in mind.

Cognition
Under a theory of event representations that defines events as dynamic changes in objects across both time and space, as in the proposal of Intersecting Object Histories (Altmann & Ekves, 2019), the encoding of changes in state is a fundamental first...

Deep learning-based reconstruction may improve non-contrast cerebral CT imaging compared to other current reconstruction algorithms.

European radiology
OBJECTIVES: To evaluate image quality and reconstruction times of a commercial deep learning reconstruction algorithm (DLR) compared to hybrid-iterative reconstruction (Hybrid-IR) and model-based iterative reconstruction (MBIR) algorithms for cerebra...

Validation of a Novel Simulation-Based Test in Robot-Assisted Radical Prostatectomy.

Journal of endourology
To investigate validity evidence for a simulator-based test in robot-assisted radical prostatectomy (RARP). The test consisted of three modules on the RobotiX Mentor VR-simulator: and . Validity evidence was investigated by using Messick's framewo...

Convolutional neural network for classifying primary liver cancer based on triple-phase CT and tumor marker information: a pilot study.

Japanese journal of radiology
PURPOSE: To develop convolutional neural network (CNN) models for differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) and predicting histopathological grade of HCC.

Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising.

NeuroImage
Automatic cerebral cortical surface reconstruction is a useful tool for cortical anatomy quantification, analysis and visualization. Recently, the Human Connectome Project and several studies have shown the advantages of using T-weighted magnetic res...