Geriatrics

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

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Subcategories: Alzheimer's Disease Medicare
Showing 211-231 of 7,162 articles
Prediction of future aging-related slow gait and its determinants with deep learning and logistic regression.

BACKGROUND: Identification of accelerated aging and its biomarkers can lead to more timely therapeut...

Artificial intelligence-derived retinal age gap as a marker for reproductive aging in women.

Reproductive aging impacts women's health through fertility decline, disease susceptibility, and sys...

Alzheimer's disease digital biomarkers multidimensional landscape and AI model scoping review.

As digital biomarkers gain traction in Alzheimer's disease (AD) diagnosis, understanding recent adva...

Rate of brain aging associates with future executive function in Asian children and older adults.

Brain age has emerged as a powerful tool to understand neuroanatomical aging and its link to health ...

Unsupervised Machine Learning-Based Process Analytical Tools for Near Real-Time Cell Morphology Analysis During CAR-T Cell Manufacturing.

Cell therapies like Chimeric Antigen Receptor (CAR)-T cell therapy deliver living cells to patients ...

Diagnostic Prediction Models for Sarcopenia: A Systematic Review and Meta-Analysis.

OBJECTIVES: Early detection and diagnosis of sarcopenia remain challenging. Despite significant prog...

Retinal Vessel Traits and Age-Related Eye Disease in the Canadian Longitudinal Study on Aging.

BACKGROUND: To cross-sectionally and longitudinally examine whether retinal vessel traits are associ...

Discovery of Novel Anti-Acetylcholinesterase Peptides Using a Machine Learning and Molecular Docking Approach.

OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medici...

Management of polypharmacy through deprescribing in older patients: a review of the role of AI tools.

INTRODUCTION: Deprescribing is crucial for improving patient safety since polypharmacy in older adul...

Optimizing Dementia Diagnosis Through Distance-Correlation Feature Space and Dimensionality Reduction.

The reduction of dimensionality in machine learning and artificial intelligence problems constitutes...

Artificial Intelligence in Chronic Disease Management for Aging Populations: A Systematic Review of Machine Learning and NLP Applications.

As China's elderly population grows rapidly and the aging society arrives, the number of elderly pat...

Massively parallel genetic perturbation suggests the energetic structure of an amyloid-β transition state.

Amyloid aggregates are pathological hallmarks of many human diseases, but how soluble proteins nucle...

Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction.

Accurate traffic flow prediction is vital for intelligent transportation systems but presents signif...

An ensemble-based 3D residual network for the classification of Alzheimer's disease.

Alzheimer's disease (AD) is a common type of dementia, with mild cognitive impairment (MCI) being a ...

Updates on inherited arrhythmia syndromes (Brugada syndrome, long QT syndrome, CPVT, ARVC).

The inherited arrhythmia (IA) syndromes are a group of rare and complex conditions that may predispo...

A cross population study of retinal aging biomarkers with longitudinal pre-training and label distribution learning.

Retinal age has emerged as a promising biomarker of aging, offering a non-invasive and accessible as...

Machine learning is changing osteoporosis detection: an integrative review.

Machine learning drives osteoporosis detection and screening with higher clinical accuracy and acces...

Detecting label noise in longitudinal Alzheimer's data with explainable artificial intelligence.

Reliable classification of cognitive states in longitudinal Alzheimer's Disease (AD) studies is crit...

A computational framework for longitudinal medication adherence prediction in breast cancer survivors: A social cognitive theory based approach.

Non-adherence to medications is a critical concern since nearly half of patients with chronic illnes...

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