Geriatrics

A review of cable-driven rehabilitation devices.

To conduct a survey on the research and development of cable-driven rehabilitation devices (CDRDs). This review searches in the databases of PubMed, IEEE Xplore Digital Library, Science Direct, and Google Scholar using various combinations of the following keywords: cable, wire, rehabilitation, assistance, therapy, training, robot, elastic, and pneumatic. Searches in the above databases for refe...

Indirect and direct training of spiking neural networks for end-to-end control of a lane-keeping vehicle.

Building spiking neural networks (SNNs) based on biological synaptic plasticities holds a promising potential for accomplishing fast and energy-efficient computing, which is beneficial to mobile robotic applications. However, the implementations of SNNs in robotic fields are limited due to the lack of practical training methods. In this paper, we therefore introduce both indirect and direct end-to...

Vertebrae Identification and Localization Utilizing Fully Convolutional Networks and a Hidden Markov Model.

Automated identification and localization of vertebrae in spinal computed tomography (CT) imaging is a complicated hybrid task. This task requires det...

Application of artificial neural network model in diagnosis of Alzheimer's disease.

BACKGROUND: Alzheimer's disease has become a public health crisis globally due to its increasing incidence. The purpose of this study was to establish...

Identifying incident dementia by applying machine learning to a very large administrative claims dataset.

Alzheimer's disease and related dementias (ADRD) are highly prevalent conditions, and prior efforts to develop predictive models have relied on demogr...

Cortical graph neural network for AD and MCI diagnosis and transfer learning across populations.

Combining machine learning with neuroimaging data has a great potential for early diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease...

Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and Longevity.

First published in 2016, predictors of chronological and biological age developed using deep learning (DL) are rapidly gaining popularity in the aging...

Mechanical Ventilation Guided by Electrical Impedance Tomography in Children With Acute Lung Injury.

OBJECTIVES: To provide proof-of-concept for a protocol applying a strategy of personalized mechanical ventilation in children with acute respiratory d...

Linguistic summarization of in-home sensor data.

INTRODUCTION: With the increase in the population of older adults around the world, a significant amount of work has been done on in-home sensor techn...

Incorporating Conversational Strategies in a Social Robot to Interact with People with Dementia.

BACKGROUND: Socially assistive robots (SARs) have the potential to assist nonpharmacological interventions based on verbal communication to support th...

Screening and Assessment of Bone Health in Indian Women Using an Indigenous ELISA of Human Osteocalcin a Bone Turnover Marker.

Osteoporosis a major public health problem of the elderly, is associated with substantial morbidity and socio economic burden. The aim of the study wa...

Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment.

OBJECTIVE: To investigate a fully automated abdominal CT-based muscle tool in a large adult screening population.

A New Approach to Fall Detection Based on Improved Dual Parallel Channels Convolutional Neural Network.

Falls are the major cause of fatal and non-fatal injury among people aged more than 65 years. Due to the grave consequences of the occurrence of falls...

Deep-learning-based imaging-classification identified cingulate island sign in dementia with Lewy bodies.

The differentiation of dementia with Lewy bodies (DLB) from Alzheimer's disease (AD) using brain perfusion single photon emission tomography is import...

Diagnosis of Alzheimer's disease with Sobolev gradient-based optimization and 3D convolutional neural network.

Alzheimer's disease is a neuropsychiatric, progressive, also an irreversible disease. There is not an effective cure for the disease. However, early d...

Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders.

Many classical machine learning techniques have been used to explore Alzheimer's disease (AD), evolving from image decomposition techniques such as pr...

Effects of extended-release eprinomectin on fescue toxicosis, performance, and reproduction on fall-calving beef cows.

The objective of this experiment was to evaluate effects of extended-release eprinomectin on fescue toxicosis and impacts on performance and reproduct...

Machine-learning based brain age estimation in major depression showing no evidence of accelerated aging.

Molecular biological findings indicate that affective disorders are associated with processes akin to accelerated aging of the brain. The use of the B...

A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data.

INTRODUCTION: It is challenging at baseline to predict when and which individuals who meet criteria for mild cognitive impairment (MCI) will ultimatel...

Fast and automatic assessment of fall risk by coupling machine learning algorithms with a depth camera to monitor simple balance tasks.

BACKGROUND: Falls in the elderly constitute a major health issue associated to population ageing. Current clinical tests evaluating fall risk mostly c...