Geriatrics

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

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Showing 1009-1029 of 7,204 articles
Metabolic dysfunctions predict the development of Alzheimer's disease: Statistical and machine learning analysis of EMR data.

INTRODUCTION: The incidence of Alzheimer's disease (AD) and obesity rise concomitantly. This study e...

Self-normalization for a 1 mmresolution clinical PET system using deep learning.

This work proposes, for the first time, an image-based end-to-end self-normalization framework for p...

Identification of medication-related fall risk in adults and older adults admitted to hospital: A machine learning approach.

The study aimed to develop and validate, through machine learning, a fall risk prediction model rela...

Artificial Intelligence for Radiation Treatment Planning: Bridging Gaps From Retrospective Promise to Clinical Reality.

Artificial intelligence (AI) radiation therapy (RT) planning holds promise for enhancing the consist...

Identification and Validation of Aging Related Genes Signature in Chronic Obstructive Pulmonary Disease.

PURPOSE: Chronic Obstructive Pulmonary Disease (COPD) is regarded as an accelerated aging disease. A...

Gender-specific factors of suicidal ideation among high school students in Yunnan province, China: A machine learning approach.

BACKGROUND: Suicidal ideation (SI) assumes a pivotal role in predicting suicidal behaviors. The inci...

Considering multi-scale built environment in modeling severity of traffic violations by elderly drivers: An interpretable machine learning framework.

The causes of traffic violations by elderly drivers are different from those of other age groups. To...

Preventive machine learning models incorporating health checkup data and hair mineral analysis for low bone mass identification.

Machine learning (ML) models have been increasingly employed to predict osteoporosis. However, the i...

End-to-end reproducible AI pipelines in radiology using the cloud.

Artificial intelligence (AI) algorithms hold the potential to revolutionize radiology. However, a si...

Machine learning-based model to predict composite thromboembolic events among Chinese elderly patients with atrial fibrillation.

OBJECTIVE: Accurate prediction of survival prognosis is helpful to guide clinical decision-making. T...

Actionable Predictions of Human Pharmacokinetics at the Drug Design Stage.

We present a novel computational approach for predicting human pharmacokinetics (PK) that addresses ...

Incremental Value of Multidomain Risk Factors for Dementia Prediction: A Machine Learning Approach.

OBJECTIVE: The current evidence regarding how different predictor domains contributes to predicting ...

Leveraging feature selection for enhanced fall risk prediction in elderly using gait analysis.

There is no effective fall risk screening tool for the elderly that can be integrated into clinical ...

Joint use of population pharmacokinetics and machine learning for prediction of valproic acid plasma concentration in elderly epileptic patients.

BACKGROUND: Valproic acid (VPA) is a commonly used broad-spectrum antiepileptic drug. For elderly ep...

Assessment of left ventricular wall thickness and dimension: accuracy of a deep learning model with prediction uncertainty.

Left ventricular (LV) geometric patterns aid clinicians in the diagnosis and prognostication of vari...

Euclidean-Distance-Preserved Feature Reduction for efficient person re-identification.

Person Re-identification (Re-ID) aims to match person images across non-overlapping cameras. The exi...

Joint computation offloading and resource allocation for end-edge collaboration in internet of vehicles via multi-agent reinforcement learning.

Vehicular edge computing (VEC), a promising paradigm for the development of emerging intelligent tra...

TS-AI: A deep learning pipeline for multimodal subject-specific parcellation with task contrasts synthesis.

Accurate mapping of brain functional subregions at an individual level is crucial. Task-based functi...

RS-Net: An end-to-end deep learning framework for rodent skull stripping in multi-center brain MRI.

Skull stripping is a crucial preprocessing step in magnetic resonance imaging (MRI), where experts m...

Targeting Machine Learning and Artificial Intelligence Algorithms in Health Care to Reduce Bias and Improve Population Health.

Policy Points Artificial intelligence (AI) is disruptively innovating health care and surpassing our...

Mapping Knowledge Landscapes and Emerging Trends in AI for Dementia Biomarkers: Bibliometric and Visualization Analysis.

BACKGROUND: With the rise of artificial intelligence (AI) in the field of dementia biomarker researc...

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