Geriatrics

Selfee, self-supervised features extraction of animal behaviors.

Fast and accurately characterizing animal behaviors is crucial for neuroscience research. Deep learn...

Machine learning for comprehensive prediction of high risk for Alzheimer's disease based on chromatic pupilloperimetry.

Currently there are no reliable biomarkers for early detection of Alzheimer's disease (AD) at the pr...

Deep convolutional neural networks for automated scoring of pentagon copying test results.

This study aims to investigate the accuracy of a fine-tuned deep convolutional neural network (CNN) ...

Deep learning for Alzheimer's disease diagnosis: A survey.

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a progressive ...

Implementation of Aging Mechanism Analysis and Prediction for XILINX 7-Series FPGAs with a 28-nm Process.

Commercial off-the-shelf (COTS) field-programmable gate arrays (FPGAs) with a 28-nm process have bec...

Multiclass Cancer Prediction Based on Copy Number Variation Using Deep Learning.

DNA copy number variation (CNV) is the type of DNA variation which is associated with various human ...

A combination model of AD biomarkers revealed by machine learning precisely predicts Alzheimer's dementia: China Aging and Neurodegenerative Initiative (CANDI) study.

INTRODUCTION: To test the utility of the "A/T/N" system in the Chinese population, we study core Alz...

Identifying pathological slices of gastric cancer via deep learning.

BACKGROUND: The accuracy of histopathology diagnosis largely depends on the pathologist's experience...

End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions.

The correct assessment and characterization of heart anatomy and functionality is usually done throu...

Neuropsychological test using machine learning for cognitive impairment screening.

OBJECTIVES: Neuropsychological tests (NPTs) are widely used tools to evaluate cognitive functioning....

Improving Recognition of Overlapping Activities with Less Interclass Variations in Smart Homes through Clustering-Based Classification.

The systems of sensing technology along with machine learning techniques provide a robust solution i...

CT-Derived Body Composition Assessment as a Prognostic Tool in Oncologic Patients: From Opportunistic Research to Artificial Intelligence-Based Clinical Implementation.

CT-based body composition measures are well established in research settings as prognostic markers i...

Application of Imaging Examination Based on Deep Learning in the Diagnosis of Viral Senile Pneumonia.

Medical image classification technology, preferably which is based on the deep learning, is not only...

Long Jump Action Recognition Based on Deep Convolutional Neural Network.

Long jump is a test item of national student physical health monitoring, which can reflect the quali...

Vision-based human fall detection systems using deep learning: A review.

Human fall is one of the very critical health issues, especially for elders and disabled people livi...

Determinants of implementing of pet robots in nursing homes for dementia care.

BACKGROUND: Pet robots have been employed as viable substitutes to pet therapy in nursing homes. Des...

Decoding neural activity preceding balance loss during standing with a lower-limb exoskeleton using an interpretable deep learning model.

Falls are a leading cause of death in adults 65 and older. Recent efforts to restore lower-limb func...

Predicting and understanding arterial elasticity from key microstructural features by bidirectional deep learning.

Microstructural features and mechanical properties are closely related in all soft biological tissue...

Confusion regarding the use of Natural Language Processing in ICU delirium assessment. Author's reply.

Hippocampal representations for deep learning on Alzheimer's disease.

Deep learning offers a powerful approach for analyzing hippocampal changes in Alzheimer's disease (A...

The perspectives of older adults with mild cognitive impairment and their caregivers on the use of socially assistive robots in healthcare: exploring factors that influence attitude in a pre-implementation stage.

BACKGROUND: Due to increasing age and an increasing prevalence rate of neurocognitive disorders such...