Geriatrics

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

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Showing 2710-2730 of 7,277 articles
The Digital Health Revolution and People with Disabilities: Perspective from the United States.

This article serves as the introduction to this special issue on Mobile Health and Mobile Rehabilita...

A Multi-Task Framework for Facial Attributes Classification through End-to-End Face Parsing and Deep Convolutional Neural Networks.

Human face image analysis is an active research area within computer vision. In this paper we propos...

Fuzzy risk prediction of roof fall and rib spalling: based on FFTA-DFCE and risk matrix methods.

The working conditions of underground mining are complex and variable, and roof fall and rib spallin...

pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.

Identification of neoantigens is a critical step in predicting response to checkpoint blockade thera...

System Design for Emergency Alert Triggered by Falls Using Convolutional Neural Networks.

The world population ageing is on the rise, which has led to an increase in the demand for medical c...

Abstractive summarization of long texts by representing multiple compositionalities with temporal hierarchical pointer generator network.

In order to tackle the problem of abstractive summarization of long multi-sentence texts, it is crit...

Forecasting one-day-forward wellness conditions for community-dwelling elderly with single lead short electrocardiogram signals.

BACKGROUND: The accelerated growth of elderly population is creating a heavy burden to the healthcar...

Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records.

Machine learning has become ubiquitous and a key technology on mining electronic health records (EHR...

Effects of medium- and long-distance running on cardiac damage markers in amateur runners: a systematic review, meta-analysis, and metaregression.

BACKGROUND: To finish an endurance race, athletes perform a vigorous effort that induces the release...

Dual-functional neural network for bilateral hippocampi segmentation and diagnosis of Alzheimer's disease.

PURPOSE: Knowing the course of Alzheimer's disease is very important to prevent the deterioration of...

Hypergraph based multi-task feature selection for multimodal classification of Alzheimer's disease.

Multi-modality based classification methods are superior to the single modality based approaches for...

A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease.

Alzheimer's disease (AD) is a progressive and irreversible brain degenerative disorder. Mild cogniti...

A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia.

Electroencephalographic (EEG) recordings generate an electrical map of the human brain that are usef...

Exploring the perceptions of people with dementia about the social robot PARO in a hospital setting.

New technology, such as social robots, opens up new opportunities in hospital settings. PARO, a robo...

Evaluating the reliability of neurocognitive biomarkers of neurodegenerative diseases across countries: A machine learning approach.

Accurate early diagnosis of neurodegenerative diseases represents a growing challenge for current cl...

Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.

Preserving cognition and mental capacity is critical to aging with autonomy. Early detection of path...

Diagnostic and Gradation Model of Osteoporosis Based on Improved Deep U-Net Network.

The measurement of bone mineral density for osteoporosis has always been the focus of researchers be...

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