Geriatrics

Care Personnel's Attitudes and Fears Toward Care Robots in Elderly Care: A Comparison of Data from the Care Personnel in Finland and Japan.

PURPOSE: The aim of the study was to analyze and compare elderly care personnel attitudes toward care robots in Finland and Japan.

Deep neural network improves fracture detection by clinicians.

Suspected fractures are among the most common reasons for patients to visit emergency departments (EDs), and X-ray imaging is the primary diagnostic tool used by clinicians to assess patients for fractures. Missing a fracture in a radiograph often has severe consequences for patients, resulting in delayed treatment and poor recovery of function. Nevertheless, radiographs in emergency settings are ...

High-Fidelity Monocular Face Reconstruction Based on an Unsupervised Model-Based Face Autoencoder.

In this work, we propose a novel model-based deep convolutional autoencoder that addresses the highly challenging problem of reconstructing a 3D human...

Vitamin D status in relation to age, bone mineral density of the spine and femur in obese Saudi females - A hospital-based study.

The aim of the present study was to evaluate the association between Bone mineral density in lumber spine and femoral neck with serum total levels of ...

End-to-End syndrome differentiation of Yin deficiency and Yang deficiency in traditional Chinese medicine.

BACKGROUND AND OBJECTIVE: Yin and Yang, two concepts adapted from classical Chinese philosophy, play a diagnostic role in Traditional Chinese Medicine...

Satisfaction and Technology Evaluation of a Telehealth Robotic Program to Optimize Healthy Independent Living for Older Adults.

BACKGROUND AND PURPOSE: With the growth in the aging population, and shortage of primary care providers, telehealth programs are needed to optimize he...

Enlarged perivascular spaces in brain MRI: Automated quantification in four regions.

Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, are common in aging, and are considered a reflection of cerebral small...

Infant Brain Development Prediction With Latent Partial Multi-View Representation Learning.

The early postnatal period witnesses rapid and dynamic brain development. However, the relationship between brain anatomical structure and cognitive a...

Predicting hospital associated disability from imbalanced data using supervised learning.

Hospitalization of elderly patients can lead to serious adverse effects on their functional capability. Identifying the underlying factors leading to ...

Deep learning based low-cost high-accuracy diagnostic framework for dementia using comprehensive neuropsychological assessment profiles.

BACKGROUND: The conventional scores of the neuropsychological batteries are not fully optimized for diagnosing dementia despite their variety and abun...

3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas.

: Identification of early-stage pulmonary adenocarcinomas before surgery, especially in cases of subcentimeter cancers, would be clinically important ...

Alzheimer's disease diagnosis based on multiple cluster dense convolutional networks.

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and cognitive functions. Structural magne...

A wearable hip-assist robot reduces the cardiopulmonary metabolic energy expenditure during stair ascent in elderly adults: a pilot cross-sectional study.

BACKGROUND: Stair ascent is one of the most important and challenging activities of daily living to maintain mobility and independence in elderly adul...

Robotics in Nursing: A Scoping Review.

PURPOSE: Driven by the shortage in qualified nurses and the high percentage of aging populations, the past decade has witnessed a significant growth i...

Artificial Intelligence Applied to Osteoporosis: A Performance Comparison of Machine Learning Algorithms in Predicting Fragility Fractures From MRI Data.

BACKGROUND: A current challenge in osteoporosis is identifying patients at risk of bone fracture.

Learning to Detect Cognitive Impairment through Digital Games and Machine Learning Techniques.

OBJECTIVE: Alzheimer's disease (AD) is one of the most prevalent diseases among the adult population. The early detection of Mild Cognitive Impairment...

Towards End-to-End ECG Classification With Raw Signal Extraction and Deep Neural Networks.

This paper proposes deep learning methods with signal alignment that facilitate the end-to-end classification of raw electrocardiogram (ECG) signals i...

Dialogue Systems and Conversational Agents for Patients with Dementia: The Human-Robot Interaction.

This study aimed to identify and describe the fundamental characteristics of spoken dialogue systems, and their role in supporting human-robot interac...

Instance-Based Representation Using Multiple Kernel Learning for Predicting Conversion to Alzheimer Disease.

The early detection of Alzheimer's disease and quantification of its progression poses multiple difficulties for machine learning algorithms. Two of t...

A Novel Deep Learning Framework on Brain Functional Networks for Early MCI Diagnosis.

Although alternations of brain functional networks (BFNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been conside...