Geriatrics

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

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Subcategories: Alzheimer's Disease Medicare
Showing 358-378 of 7,162 articles
Predicting and Evaluating Cognitive Status in Aging Populations Using Decision Tree Models.

To improve the identification of cognitive impairment by distinguishing normal cognition (NC), mild...

Cognitive impairment screening strategy to reduce the burden of Alzheimer's disease in Shanghai: A system dynamics approach.

BACKGROUND: Population aging increases the economic burden of Alzheimer's disease (AD). Early screen...

Assessing large language model performance related to aging in genetic conditions.

Most genetic conditions are described in pediatric populations, leaving a gap in understanding their...

Deep Learning-enhanced Opportunistic Osteoporosis Screening in Ultralow-Voltage (80 kV) Chest CT: A Preliminary Study.

RATIONALE AND OBJECTIVES: To explore the feasibility of deep learning (DL)-enhanced, fully automated...

Ensemble Learning-Based Alzheimer's Disease Classification Using Electroencephalogram Signals and Clock Drawing Test Images.

Ensemble learning (EL), a machine learning technique that combines the results of multiple learning ...

Assessing the Content of Goals of Care Documentation for Hospitalized Patients With Alzheimer's Disease and Related Dementias.

BACKGROUND: Goals of care (GOC) conversations are an evidence-based practice that help clarify and a...

How Can Anomalous-Diffusion Neural Networks Under Connectomics Generate Optimized Spatiotemporal Dynamics.

Spatiotemporal dynamics in the brain have been recognized as strongly related to the formation of pe...

Modality-Aware Discriminative Fusion Network for Integrated Analysis of Brain Imaging Genomics.

Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD), characterized...

Deep Profiling of Oocyte Aging Enabled by Simple One-Step Vial-Based Pretreatment and Single-Cell Proteomics.

Single-cell proteomics is a pivotal technology for studying cellular phenotypes, offering unparallel...

Machine Learning Multimodal Model for Delirium Risk Stratification.

IMPORTANCE: Automating the identification of risk for developing hospital delirium with models that ...

Exploring Suitability of Low-Severity Rating Hospital Incident Reports for Machine Learning.

Electronic incident reporting is a key quality and a safety process for healthcare organizations tha...

Gender Authorship Among Urology Artificial Intelligence Publications: A 10-Year Retrospective Analysis.

We aim to characterize gender authorship in urology-related artificial intelligence (AI) research. A...

Interpretable unsupervised neural network structure for data clustering via differentiable reconstruction of ONMF and sparse autoencoder.

Neural networks, while powerful, often face significant challenges in terms of interpretability, par...

Alzheimer's disease knowledge graph enhances knowledge discovery and disease prediction.

OBJECTIVE: To construct an Alzheimer's Disease Knowledge Graph (ADKG) by extracting and integrating ...

Intelligent predictive risk assessment and management of sarcopenia in chronic disease patients using machine learning and a web-based tool.

BACKGROUND: Individuals with chronic diseases are at higher risk of sarcopenia, and precise predicti...

Evaluating the Chinese versions of delirium assessment scales: a diagnostic systematic review.

BACKGROUND: The purpose of this study is to examine the validity, reliability and methodological qua...

AI in Home Care-Evaluation of Large Language Models for Future Training of Informal Caregivers: Observational Comparative Case Study.

BACKGROUND: The aging population presents an accomplishment for society but also poses significant c...

A novel diagnosis method utilizing MDBO-SVM and imaging genetics for Alzheimer's disease.

Alzheimer's disease (AD) is the most common neurodegenerative disorder, yet its underlying mechanism...

Biological age prediction in schizophrenia using brain MRI, gut microbiome and blood data.

The study of biological age prediction using various biological data has been widely explored. Howev...

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