Geriatrics

Wide and deep learning based approaches for classification of Alzheimer's disease using genome-wide association studies.

The increasing incidence of Alzheimer's disease (AD) has been leading towards a significant growth i...

The long path ahead of robotics in psychiatry.

Decoding Silent Speech Based on High-Density Surface Electromyogram Using Spatiotemporal Neural Network.

Finer-grained decoding at a phoneme or syllable level is a key technology for continuous recognition...

Implementing PainChek and PARO to Support Pain Assessment and Management in Residents with Dementia: A Qualitative Study.

BACKGROUND: Pain is a common problem but often undiagnosed and untreated in people with dementia.

A long distance telesurgical demonstration on robotic surgery phantoms over 5G.

PURPOSE: Using robotic technology and communications infrastructure to remotely perform surgery has ...

Assessment of Awareness, Perceptions, and Opinions towards Artificial Intelligence among Healthcare Students in Riyadh, Saudi Arabia.

: The role of the pharmacist in healthcare society is unique, since they are providers of health inf...

Revolutionizing the Early Detection of Alzheimer's Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning.

Alzheimer's disease (AD) is now classified as a silent pandemic due to concerning current statistics...

High performance for bone age estimation with an artificial intelligence solution.

PURPOSE: The purpose of this study was to compare the performance of an artificial intelligence (AI)...

Identifying fetal status with fetal heart rate: Deep learning approach based on long convolution.

CTG (Cardiotocography) is an effective tool for fetal status assessment. Clinically, doctors mainly ...

XAI-enabled neural network analysis of metabolite spatial distributions.

We used deep neural networks to process the mass spectrometry imaging (MSI) data of mouse muscle (yo...

Deep learning methods for medical image fusion: A review.

The image fusion methods based on deep learning has become a research hotspot in the field of comput...

The effect of variable labels on deep learning models trained to predict breast density.

. High breast density is associated with reduced efficacy of mammographic screening and increased ri...

Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot.

Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor functi...

Aging-related volume changes in the brain and cerebrospinal fluid using artificial intelligence-automated segmentation.

OBJECTIVES: To verify the reliability of the volumes automatically segmented using a new artificial ...

Experimental Study: Deep Learning-Based Fall Monitoring among Older Adults with Skin-Wearable Electronics.

Older adults are more vulnerable to falling due to normal changes due to aging, and their falls are ...

Understanding the Impact of Aging on Attractiveness Using a Machine Learning Model of Facial Age Progression.

Advances in machine learning age progression technology offer the unique opportunity to better unde...

Stereology neuron counts correlate with deep learning estimates in the human hippocampal subregions.

Hippocampal subregions differ in specialization and vulnerability to cell death. Neuron death and hi...

A unique color-coded visualization system with multimodal information fusion and deep learning in a longitudinal study of Alzheimer's disease.

PURPOSE: Automated diagnosis and prognosis of Alzheimer's Disease remain a challenging problem that ...

Machine and deep learning-based clinical characteristics and laboratory markers for the prediction of sarcopenia.

BACKGROUND: Sarcopenia is an age-related progressive skeletal muscle disorder involving the loss of ...

Artificial intelligence assisted identification of potential tau aggregation inhibitors: ligand- and structure-based virtual screening, in silico ADME, and molecular dynamics study.

Alzheimer's disease (AD) is a severe, growing, multifactorial disorder affecting millions of people ...

Comparison of End-to-End Neural Network Architectures and Data Augmentation Methods for Automatic Infant Motility Assessment Using Wearable Sensors.

Infant motility assessment using intelligent wearables is a promising new approach for assessment of...