AIMC Topic: Aged, 80 and over

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Detecting Vascular Age Using the Analysis of Peripheral Pulse.

IEEE transactions on bio-medical engineering Mar 9, 2018
UNLABELLED: Vascular ageing is known to be accompanied by arterial stiffening and vascular endothelial dysfunction, and represents an independent factor contributing to the development of cardiovascular disease. The microvascular pulse is affected by...
Laser-Doppler Flowmetry Pulse Microvessels Algorithms Infant, Newborn Child, Preschool Humans Adult Aged Child Aged, 80 and over Support Vector Machine Aging Young Adult Pulse Wave Analysis Middle Aged Signal Processing, Computer-Assisted Infant Adolescent
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Age-related changes in the ease of dynamical transitions in human brain activity.

Human brain mapping Mar 9, 2018
Executive functions, a set of cognitive processes that enable flexible behavioral control, are known to decay with aging. Because such complex mental functions are considered to rely on the dynamic coordination of functionally different neural system...
Brain Female Aged Aged, 80 and over Young Adult Humans Neural Networks, Computer Magnetic Resonance Imaging Brain Mapping Adult Oxygen Male Aging Middle Aged Image Processing, Computer-Assisted Nonlinear Dynamics Neural Pathways Executive Function
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A Novel Neural Network Model for Blood Pressure Estimation Using Photoplethesmography without Electrocardiogram.

Journal of healthcare engineering Mar 7, 2018
The prevention, evaluation, and treatment of hypertension have attracted increasing attention in recent years. As photoplethysmography (PPG) technology has been widely applied to wearable sensors, the noninvasive estimation of blood pressure (BP) usi...
Middle Aged Diastole Aged Hypertension Aged, 80 and over Blood Pressure Photoplethysmography Young Adult Pulse Wave Analysis Electrocardiography Adult Humans Critical Care Blood Pressure Determination Male Pattern Recognition, Automated Neural Networks, Computer Systole Databases, Factual Female Reproducibility of Results
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Prediction of rupture risk in anterior communicating artery aneurysms with a feed-forward artificial neural network.

European radiology Feb 23, 2018
OBJECTIVES: Anterior communicating artery (ACOM) aneurysms are the most common intracranial aneurysms, and predicting their rupture risk is challenging. We aimed to predict this risk using a two-layer feed-forward artificial neural network (ANN).
Aneurysm, Ruptured Intracranial Aneurysm Anterior Cerebral Artery Young Adult Neural Networks, Computer Age Factors Adult Models, Biological Female Male Decision Making Computed Tomography Angiography Risk Factors Middle Aged Predictive Value of Tests Cerebral Angiography Aged ROC Curve Humans Aged, 80 and over
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Predictors of activities of daily living outcomes after upper limb robot-assisted therapy in subacute stroke patients.

PloS one Feb 21, 2018
BACKGROUND: Upper limb recovery is one of the main goals of post-stroke rehabilitation due to its importance for autonomy in Activities of Daily Living (ADL). Although the efficacy of upper limb Robot-assisted Therapy (RT) is well established in lite...
Aged, 80 and over Adult Male Middle Aged Stroke Rehabilitation Adolescent Humans Robotics Retrospective Studies Stroke Female Exercise Therapy Aged Activities of Daily Living Upper Extremity
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Using Machine Learning and a Combination of Respiratory Flow, Laryngeal Motion, and Swallowing Sounds to Classify Safe and Unsafe Swallowing.

IEEE transactions on bio-medical engineering Feb 19, 2018
OBJECTIVE: The aim of this research was to develop a swallowing assessment method to help prevent aspiration pneumonia. The method uses simple sensors to monitor swallowing function during an individual's daily life.
Machine Learning Female Aged Aged, 80 and over Young Adult Adult Male Middle Aged Monitoring, Physiologic Signal Processing, Computer-Assisted Humans Respiration Deglutition Disorders Deglutition Larynx
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Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning.

Nature biomedical engineering Feb 19, 2018
Traditionally, medical discoveries are made by observing associations, making hypotheses from them and then designing and running experiments to test the hypotheses. However, with medical images, observing and quantifying associations can often be di...
Deep Learning Fundus Oculi Retina Image Interpretation, Computer-Assisted Humans Aged Algorithms Aged, 80 and over Female Male Risk Factors Cardiovascular Diseases Middle Aged
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Safety and Feasibility of a Novel Active Fixation Temporary Pacing Lead.

The Journal of invasive cardiology Feb 15, 2018
OBJECTIVE: This first-in-human study evaluated the safety and technical feasibility of the Tempo temporary cardiac pacing lead (BioTrace Medical), which includes a novel fixation mechanism and soft tip.
Aged Aged, 80 and over Male Middle Aged Electrocardiography Robotics Humans Female Surgery, Computer-Assisted Heart Conduction System Magnetics Tachycardia, Supraventricular
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Predicting sex from brain rhythms with deep learning.

Scientific reports Feb 15, 2018
We have excellent skills to extract sex from visual assessment of human faces, but assessing sex from human brain rhythms seems impossible. Using deep convolutional neural networks, with unique potential to find subtle differences in apparent similar...
Aged, 80 and over Adult Male Middle Aged Deep Learning Humans Brain Female Aged Adolescent Electroencephalography Sex Characteristics
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Predicting Visual Acuity by Using Machine Learning in Patients Treated for Neovascular Age-Related Macular Degeneration.

Ophthalmology Feb 14, 2018
PURPOSE: To predict, by using machine learning, visual acuity (VA) at 3 and 12 months in patients with neovascular age-related macular degeneration (AMD) after initial upload of 3 anti-vascular endothelial growth factor (VEGF) injections.
Choroidal Neovascularization Aged, 80 and over Male Middle Aged Disease Progression Angiogenesis Inhibitors Follow-Up Studies Algorithms Visual Acuity Databases, Factual Vascular Endothelial Growth Factor A Humans Female Intravitreal Injections Machine Learning Reproducibility of Results Wet Macular Degeneration Aged
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