Geriatrics

Deep biomarkers of aging and longevity: from research to applications.

Multiple recent advances in machine learning enabled computer systems to exceed human performance in many tasks including voice, text, and speech recognition and complex strategy games. Aging is a complex multifactorial process driven by and resulting in the many minute changes transpiring at every level of the human organism. Deep learning systems trained on the many measurable features changing ...

The exploration of feature extraction and machine learning for predicting bone density from simple spine X-ray images in a Korean population.

OBJECTIVE: Osteoporosis is hard to detect before it manifests symptoms and complications. In this study, we evaluated machine learning models for identifying individuals with abnormal bone mineral density (BMD) through an analysis of spine X-ray features extracted by deep learning to alert high-risk osteoporosis populations.

MedGAN: Medical image translation using GANs.

Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications. However, a large...

A general end-to-end diagnosis framework for manufacturing systems.

The manufacturing sector is envisioned to be heavily influenced by artificial-intelligence-based technologies with the extraordinary increases in comp...

Evaluation of Balance and Fall Risk in Patients with Plantar Fasciitis Syndrome.

OBJECTIVES: In this study, we aimed to investigate plantar fasciitis syndrome on balance and the risks of the falls.

IoT-Enabled Dual-Arm Motion Capture and Mapping for Telerobotics in Home Care.

With the paradigm shift from hospital-centric healthcare to home-centric healthcare in Healthcare 4.0, healthcare robotics has become one of the faste...

Real-Time Extraction of Important Surgical Phases in Cataract Surgery Videos.

The present study aimed to conduct a real-time automatic analysis of two important surgical phases, which are continuous curvilinear capsulorrhexis (C...

Genome-wide prediction and prioritization of human aging genes by data fusion: a machine learning approach.

BACKGROUND: Machine learning can effectively nominate novel genes for various research purposes in the laboratory. On a genome-wide scale, we implemen...

SegAE: Unsupervised white matter lesion segmentation from brain MRIs using a CNN autoencoder.

White matter hyperintensities (WMHs) of presumed vascular origin are frequently observed in magnetic resonance images (MRIs) of the elderly. Detection...

Wearable Fall Detector Using Recurrent Neural Networks.

Falls have become a relevant public health issue due to their high prevalence and negative effects in elderly people. Wearable fall detector devices a...

Fall Risk Prediction in Multiple Sclerosis Using Postural Sway Measures: A Machine Learning Approach.

Numerous postural sway metrics have been shown to be sensitive to balance impairment and fall risk in individuals with MS. Yet, there are no guideline...

Quantitative susceptibility mapping based hybrid feature extraction for diagnosis of Parkinson's disease.

Parkinson's disease is the second most common neurodegenerative disease in the elderly after Alzheimer's disease. The aetiology and pathogenesis of Pa...

Unsupervised 3D End-to-End Medical Image Registration With Volume Tweening Network.

3D medical image registration is of great clinical importance. However, supervised learning methods require a large amount of accurately annotated cor...

A distributed multitask multimodal approach for the prediction of Alzheimer's disease in a longitudinal study.

Predicting the progression of Alzheimer's Disease (AD) has been held back for decades due to the lack of sufficient longitudinal data required for the...

Single-slice Alzheimer's disease classification and disease regional analysis with Supervised Switching Autoencoders.

BACKGROUND: Alzheimer's disease (AD) is a difficult to diagnose pathology of the brain that progressively impairs cognitive functions. Computer-assist...

Qualitative, Exploratory, and Multidimensional Study of Telepresence Robots for Overcoming Social Isolation of Children and Adolescents Hospitalized in Onco-Hematology.

Treatment of pediatric cancers and hematological malignancies requires long periods of isolation in a sterile room. To promote family connections, te...

A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset.

The automatic recognition of human falls is currently an important topic of research for the computer vision and artificial intelligence communities. ...

A comparison of machine learning classifiers for dementia with Lewy bodies using miRNA expression data.

BACKGROUND: Dementia with Lewy bodies (DLB) is the second most common subtype of neurodegenerative dementia in humans following Alzheimer's disease (A...

Computational modeling of the effects of EEG volume conduction on functional connectivity metrics. Application to Alzheimer's disease continuum.

OBJECTIVE: The aim of this study was to evaluate the effect of electroencephalographic (EEG) volume conduction in different measures of functional con...

MCADNNet: Recognizing Stages of Cognitive Impairment through Efficient Convolutional fMRI and MRI Neural Network Topology Models.

Mild cognitive impairment (MCI) represents the intermediate stage between normal cerebral aging and dementia associated with Alzheimer's disease (AD)....