Geriatrics

Latest AI and machine learning research in geriatrics for healthcare professionals.

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Showing 2332-2352 of 7,270 articles
Thoracic Point-of-Care Ultrasound: A SARS-CoV-2 Data Repository for Future Artificial Intelligence and Machine Learning.

Current experience suggests that artificial intelligence (AI) and machine learning (ML) may be usefu...

Speech Vision: An End-to-End Deep Learning-Based Dysarthric Automatic Speech Recognition System.

Dysarthria is a disorder that affects an individual's speech intelligibility due to the paralysis of...

Detection of Postural Control in Young and Elderly Adults Using Deep and Machine Learning Methods with Joint-Node Plots.

Postural control decreases with aging. Thus, an efficient and accurate method of detecting postural ...

CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction.

Residue co-evolution has become the primary principle for estimating inter-residue distances of a pr...

A machine learning approach to screen for preclinical Alzheimer's disease.

Combining multimodal biomarkers could help in the early diagnosis of Alzheimer's disease (AD). We in...

White matter hyperintensities segmentation using the ensemble U-Net with multi-scale highlighting foregrounds.

White matter hyperintensities (WMHs) are abnormal signals within the white matter region on the huma...

Pharm-AutoML: An open-source, end-to-end automated machine learning package for clinical outcome prediction.

Although there is increased interest in utilizing machine learning (ML) to support drug development,...

A Pilot Study to Detect Agitation in People Living with Dementia Using Multi-Modal Sensors.

People living with dementia (PLwD) often exhibit behavioral and psychological symptoms, such as epis...

Humanoid socially assistive robots in dementia care: a qualitative study about expectations of caregivers and dementia trainers.

OBJECTIVE: To examine the expectations of informal caregivers, nurses, and dementia trainers regardi...

Diagnosis of Alzheimer's Disease Severity with fMRI Images Using Robust Multitask Feature Extraction Method and Convolutional Neural Network (CNN).

The automatic diagnosis of Alzheimer's disease plays an important role in human health, especially i...

ELVISort: encoding latent variables for instant sorting, an artificial intelligence-based end-to-end solution.

The growing number of recording sites of silicon-based probes means that an increasing amount of neu...

Development Issues of Healthcare Robots: Compassionate Communication for Older Adults with Dementia.

Although progress is being made in affective computing, issues remain in enabling the effective expr...

Machine learning-based modeling to predict inhibitors of acetylcholinesterase.

Acetylcholinesterase enzyme is responsible for the degradation of acetylcholine and is an important ...

Diagnosis of Alzheimer's Disease by Time-Dependent Power Spectrum Descriptors and Convolutional Neural Network Using EEG Signal.

Using strategies that obtain biomarkers where early symptoms coincide, the early detection of Alzhei...

Development of a Planar Haptic Robot With Minimized Impedance.

Several studies have reported that stroke survivors displayed improved voluntary planar movements wh...

A deep learning system for automated, multi-modality 2D segmentation of vertebral bodies and intervertebral discs.

PURPOSE: Fractures in vertebral bodies are among the most common complications of osteoporosis and o...

Improving brain age estimates with deep learning leads to identification of novel genetic factors associated with brain aging.

To study genetic factors associated with brain aging, we first need to quantify brain aging. Statist...

Unsupervised foveal vision neural architecture with top-down attention.

Deep learning architectures are an extremely powerful tool for recognizing and classifying images. H...

Novel criteria to classify ARDS severity using a machine learning approach.

BACKGROUND: Usually, arterial oxygenation in patients with the acute respiratory distress syndrome (...

A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.

Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully automated de...

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