AIMC Topic: Humans
Showing 64331 to 64340 of 95995 articles
On-Site Computed Tomography-Derived Fractional Flow Reserve Using a Machine-Learning Algorithm - Clinical Effectiveness in a Retrospective Multicenter Cohort.
Circulation journal : official journal of the Japanese Circulation Society
Jun 8, 2019
BACKGROUND: This study evaluated the diagnostic capability of on-site coronary computed tomography-derived computational fractional flow reserve (CT-FFR) determinations for detecting coronary artery disease (CAD), as assessed by invasive fractional f...
An Ontology to Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked Content.
Nutrients
Jun 8, 2019
BACKGROUND: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research out...
DRRNet: Dense Residual Refine Networks for Automatic Brain Tumor Segmentation.
Journal of medical systems
Jun 8, 2019
Glioma is one of the most common and aggressive brain tumors. Segmentation and subsequent quantitative analysis of brain tumor MRI are routine and crucial for treatment. Due to the time-consuming and tedious manual segmentation, automatic segmentatio...
Improving the repeatability of two-rate model parameter estimations by using autoencoder networks.
Progress in brain research
Jun 8, 2019
The adaptive changes elicited in visuomotor adaptation experiments are usually well explained at group level by two-rate models (Smith et al., 2006), but parameters fitted to individuals show considerable variance. Data cleaning can mitigate this pro...
Quality of working life from the perspective of different groups of professionals working in a maternity hospital.
Ciencia & saude coletiva
Jun 7, 2019
The relationship between people and work has a direct impact on quality of life and health. The objective of this article is to compare perceived levels of Quality of Working Life (QWL) across three different groups of professionals. Cross-sectional ...
FriWalk robotic walker: usability, acceptance and UX evaluation after a pilot study in a real environment.
Disability and rehabilitation. Assistive technology
Jun 7, 2019
: Scientific evidence supports that prevention strategies like multicomponent physical exercise help avoiding functional decline, falls and frailty. The robotic walker FriWalk, developed within the ACANTO project, supports the execution of controlled...
A Smart Dental Health-IoT Platform Based on Intelligent Hardware, Deep Learning, and Mobile Terminal.
IEEE journal of biomedical and health informatics
Jun 7, 2019
The dental disease is a common disease for a human. Screening and visual diagnosis that are currently performed in clinics possibly cost a lot in various manners. Along with the progress of the Internet of Things (IoT) and artificial intelligence, th...
Automatic brain tissue segmentation in fetal MRI using convolutional neural networks.
Magnetic resonance imaging
Jun 7, 2019
MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development. The cornerstone of volumetric and morphologic analysis in fetal MRI is segmentation of the fetal brain into different tissue classes. Manual segment...
Looking to the future: Learning from experience, averting catastrophe.
Neural networks : the official journal of the International Neural Network Society
Jun 7, 2019
As humans go through life sifting vast quantities of complex information, we extract knowledge from settings that are more ambiguous than our early homes and classrooms. Learning from experience in an individual's unique context generally improves ex...
Machine learning approaches for risk assessment of peripherally inserted Central catheter-related vein thrombosis in hospitalized patients with cancer.
International journal of medical informatics
Jun 7, 2019
OBJECTIVE: The aim of this study was to conduct an effective assessment of peripherally inserted central venous catheter (PICC)-related thrombosis based on machine learning (ML) techniques considering genotype.
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