Geriatrics

The Impact of Wireless Network Mobile Devices on College Students' Labour Concept Education in Artificial Intelligence Environment.

To cultivate correct labour values and good labour quality of college students and effectively promote the development of their labour concept education, this work explores the impact of wireless network mobile devices on college students' labour concept education under the environment of artificial intelligence. Firstly, a questionnaire survey is used to investigate the labour concept of 400 coll...

Age-Related Changes in Functional Connectivity during the Sensorimotor Integration Detected by Artificial Neural Network.

Large-scale functional connectivity is an important indicator of the brain's normal functioning. The abnormalities in the connectivity pattern can be used as a diagnostic tool to detect various neurological disorders. The present paper describes the functional connectivity assessment based on artificial intelligence to reveal age-related changes in neural response in a simple motor execution task....

Analysis of Factors Affecting Cranial Nerve Function of Patients With Vascular Mild Cognitive Impairment Through Functional Magnetic Resonance Imaging Under Artificial Intelligence Environment.

The study aimed to explore the risk factors of effects of patients with vascular mild cognitive impairment (VaMCI) through functional magnetic resonan...

Deep Learning-Based Electrocardiograph in Evaluating Radiofrequency Ablation for Rapid Arrhythmia.

This study is aimed at analyzing the important role of deep learning-based electrocardiograph (ECG) in the efficacy evaluation of radiofrequency ablat...

An end-to-end computer vision methodology for quantitative metallography.

Metallography is crucial for a proper assessment of material properties. It mainly involves investigating the spatial distribution of grains and the o...

Ethical Design and Use of Robotic Care of the Elderly.

The Australian Royal Commission into Aged Care Quality and Safety acknowledged understaffing and substandard care in residential aged care and home ca...

Validation of a deep learning segmentation algorithm to quantify the skeletal muscle index and sarcopenia in metastatic renal carcinoma.

OBJECTIVES: To validate a deep learning (DL) algorithm for measurement of skeletal muscular index (SMI) and prediction of overall survival in oncology...

Designing Robots for Elderly from the Perspective of Potential End-Users: A Sociological Approach.

The proposed research aims to investigate the problem of age-friendly robot designing from the perspective of the potential end-users. The initial obj...

Data-Driven Haptic Texture Modeling and Rendering Based on Deep Spatio-Temporal Networks.

Data-driven approaches are commonly used to model and render haptic textures for rigid stylus-based interaction. Current state-of-the-art data-driven ...

Signed random walk diffusion for effective representation learning in signed graphs.

How can we model node representations to accurately infer the signs of missing edges in a signed social graph? Signed social graphs have attracted con...

Impact of the training loss in deep learning-based CT reconstruction of bone microarchitecture.

PURPOSE: Computed tomography (CT) is a technique of choice to image bone structure at different scales. Methods to enhance the quality of degraded rec...

Network analytics and machine learning for predicting length of stay in elderly patients with chronic diseases at point of admission.

BACKGROUND: An aging population with a burden of chronic diseases puts increasing pressure on health care systems. Early prediction of the hospital le...

Neuroprotective and Therapeutic Effects of Tocovid and Twendee-X on Aβ Oligomer-Induced Damage in the SH-SY5Y Cell Line.

BACKGROUND: Alzheimer's disease (AD) is the most frequent cause of dementia among the elderly. The accumulation of amyloid beta (Aβ) and its downstrea...

Editorial Comment: Pediatric Sarcopenia-Quest for Diagnosis.

MCG-Net: End-to-End Fine-Grained Delineation and Diagnostic Classification of Cardiac Events From Magnetocardiographs.

In this paper, we propose an end-to-end deep learning architecture, referred as MCG-Net, integrating convolutional neural network (CNN) with transform...

Deep Learning-based Artificial Intelligence Improves Accuracy of Error-prone Lung Nodules.

Early detection of lung cancer is one way to improve outcomes. Improving the detection of nodules on chest CT scans is important. Previous artificial...

Fully automated deep-learning section-based muscle segmentation from CT images for sarcopenia assessment.

AIM: To develop a fully automated deep-learning-based approach to measure muscle area for assessing sarcopenia on standard-of-care computed tomography...

Adversarial Joint-Learning Recurrent Neural Network for Incomplete Time Series Classification.

Incomplete time series classification (ITSC) is an important issue in time series analysis since temporal data often has missing values in practical a...

Deep learning based sarcopenia prediction from shear-wave ultrasonographic elastography and gray scale ultrasonography of rectus femoris muscle.

We aim to evaluate the performance of a deep convolutional neural network (DCNN) in predicting the presence or absence of sarcopenia using shear-wave ...

Cognitive Impairment of Patient With Neurological Cerebrovascular Disease Using the Artificial Intelligence Technology Guided by MRI.

This study was to explore the application of MRI based on artificial intelligence technology combined with neuropsychological assessment to the cognit...