Geriatrics

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

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Subcategories: Alzheimer's Disease Medicare
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Improving Multiscale Fuzzy Entropy Robustness in EEG-Based Alzheimer's Disease Detection via Amplitude Transformation.

This study investigates the effectiveness of amplitude transformation in enhancing the performance a...

AlzGenPred - CatBoost-based gene classifier for predicting Alzheimer's disease using high-throughput sequencing data.

AD is a progressive neurodegenerative disorder characterized by memory loss. Due to the advancement ...

In-Home Gait Abnormality Detection Through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning.

Detecting gait abnormalities is crucial for assessing fall risks and early identification of neuromu...

Comparing effects of wearable robot-assisted gait training on functional changes and neuroplasticity: A preliminary study.

Robot-assisted gait training (RAGT) is a promising technique for improving the gait ability of elder...

Exploiting the features of deep residual network with SVM classifier for human posture recognition.

Over the last decade, there have been a lot of advances in the area of human posture recognition. Am...

Validation requirements for AI-based intervention-evaluation in aging and longevity research and practice.

The field of aging and longevity research is overwhelmed by vast amounts of data, calling for the us...

Diagnostic accuracy of deep learning in prediction of osteoporosis: a systematic review and meta-analysis.

BACKGROUND: Osteoporosis is one of the most common metabolic diseases that is characterized by a dec...

Prediction of prolonged mechanical ventilation in the intensive care unit via machine learning: a COVID-19 perspective.

Early recognition of risk factors for prolonged mechanical ventilation (PMV) could allow for early c...

[The future of medicine: an informed look into the "crystal ball"].

This article explores potential future scenarios for the medical field based on current trends, tech...

Deep learning analysis of fMRI data for predicting Alzheimer's Disease: A focus on convolutional neural networks and model interpretability.

The early detection of Alzheimer's Disease (AD) is thought to be important for effective interventio...

A Machine learning classification framework using fused fractal property feature vectors for Alzheimer's disease diagnosis.

Alzheimer's disease (AD) profoundly affects brain tissue and network structures. Analyzing the topol...

Discovering geroprotectors through the explainable artificial intelligence-based platform AgeXtend.

Aging involves metabolic changes that lead to reduced cellular fitness, yet the role of many metabol...

Assessing Locomotive Syndrome Through Instrumented Five-Time Sit-to-Stand Test and Machine Learning.

Locomotive syndrome (LS) refers to a condition where individuals face challenges in performing activ...

Portable, low-field magnetic resonance imaging for evaluation of Alzheimer's disease.

Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care as...

Bioinspired design and validation of a soft robotic end-effector with integrated shape memory alloy-driven suction capabilities.

The exploration of adaptive robotic systems capable of performing complex tasks in unstructured envi...

LCGNet: Local Sequential Feature Coupling Global Representation Learning for Functional Connectivity Network Analysis With fMRI.

Analysis of functional connectivity networks (FCNs) derived from resting-state functional magnetic r...

Brain Network Classification for Accurate Detection of Alzheimer's Disease via Manifold Harmonic Discriminant Analysis.

Mounting evidence shows that Alzheimer's disease (AD) manifests the dysfunction of the brain network...

A Machine Learning-Based Prediction Model for the Probability of Fall Risk Among Chinese Community-Dwelling Older Adults.

Fall is a common adverse event among older adults. This study aimed to identify essential fall facto...

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