Geriatrics

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

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Showing 3655-3675 of 7,397 articles
Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers.

Generative approaches for cross-modality transformation have recently gained significant attention i...

A Regression Framework for Predicting Cognitive Decline in Frontotemporal Dementia using Recurrent Neural Networks.

Frontotemporal dementia (FTD) is a progressive neurodegenerative disorder with a diverse range of sy...

Computer vision-inspired contrastive learning for self-supervised anomaly detection in sensor-based remote healthcare monitoring.

Sensor-based remote healthcare monitoring is a promising approach for timely detection of adverse he...

Machine Learning Approach for Music Familiarity Classification with Single-Channel EEG.

Recognition of familiar music on brainwaves through machine learning (ML) can be instrumental in inn...

Video-based Clinical Gait Analysis in Parkinson's Disease: A Novel Approach Using Frontal Plane Videos and Machine Learning.

Gait can be significantly impaired by neurological conditions such as Parkinson's disease (PD). Gait...

Artificial Intelligence Based Hierarchical Classification of Frontotemporal Dementia.

Frontotemporal dementia (FTD) is a typical kind of presenile dementia with three main subtypes: beha...

3D Multi-feature fusion convolutional network for Alzheimer's disease diagnosis.

The cognitive decline caused by Alzheimer's disease (AD) is closely related to the structural change...

Novel Alzheimer's Disease Stating Based on Comorbidities-Informed Graph Neural Networks.

Alzheimer's Disease (AD), the most prevalent form of dementia, requires early prediction for timely ...

Vascular Age Evaluation Enhanced using Recurrence Plot Analysis and Convolutional Neural Networks: An in-Silico Study.

Aging contributes as a major nonreversible risk factor for cardiovascular disease. This underscores ...

Identifying Prediabetes in Canadian Populations Using Machine Learning.

Prediabetes is a critical health condition characterized by elevated blood glucose levels that fall ...

Dual Attention Graph Convolutional Network Fusing Imaging and Genetic Data for Early Alzheimer's Disease Diagnosis.

Alzheimer's Disease (AD) poses a significant global neurodegenerative challenge, underscoring the ur...

Deep STI: Deep Stochastic Time-series Imputation on Electronic Health Records.

Electronic Health Records (EHRs) are a cornerstone of modern healthcare analytics, offering rich dat...

A Deep-Learning-Based Approach for Delirium Monitoring in ICU Patients Using Thermograms.

Patients in the ICU frequently suffer from delirium, which can delay their recovery and may cause si...

Graph-based deep learning models in the prediction of early-stage Alzheimers.

Alzheimer's disease is the most common age-related problem and progresses in different stages, from ...

Implementation of a machine learning model in acute coronary syndrome and stroke risk assessment for patients with lower urinary tract symptoms.

OBJECTIVE: The global population is aging and the burden of lower urinary tract symptoms (LUTS) is e...

Deep Learning-Based Vascular Aging Prediction From Retinal Fundus Images.

PURPOSE: The purpose of this study was to establish and validate a deep learning model to screen vas...

[An ensemble model for assisting early Alzheimer's disease diagnosis based on structural magnetic resonance imaging with dual-time-point fusion].

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder. Due to the subtlety of symptom...

Artificial intelligence for automatic detection of basal cell carcinoma from frozen tissue tangential biopsies.

Evaluation of basal cell carcinoma (BCC) involves tangential biopsies of a suspicious lesion that is...

Machine learning in time-lapse imaging to differentiate embryos from young vs old mice†.

Time-lapse microscopy for embryos is a non-invasive technology used to characterize early embryo dev...

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