Geriatrics

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

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Showing 3991-4011 of 7,387 articles
PTML Modeling for Alzheimer's Disease: Design and Prediction of Virtual Multi-Target Inhibitors of GSK3B, HDAC1, and HDAC6.

BACKGROUND: Alzheimer's disease is characterized by a progressive pattern of cognitive and functiona...

Robotic Systems Involved in the Diagnosis of Neurodegenerative Diseases.

The continuing development of robotics on the one hand and, on the other hand, the estimated relativ...

Multivariate Data Analysis and Machine Learning for Prediction of MCI-to-AD Conversion.

There has always been a need for discovering efficient and dependable Alzheimer's disease (AD) diagn...

Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer's Disease Gene Expression Data.

BACKGROUND: Gene Ontology (GO) is a major bioinformatic resource used for analysis of large biomedic...

Classification of Alzheimer's Disease with Respect to Physiological Aging with Innovative EEG Biomarkers in a Machine Learning Implementation.

BACKGROUND: Several studies investigated clinical and instrumental differences to make diagnosis of ...

Integrating Convolutional Neural Networks and Multi-Task Dictionary Learning for Cognitive Decline Prediction with Longitudinal Images.

BACKGROUND: Disease progression prediction based on neuroimaging biomarkers is vital in Alzheimer's ...

Artificial Intelligence in Ophthalmology: Evolutions in Asia.

Artificial intelligence (AI) has been studied in ophthalmology since availability of digital informa...

Predicting Cognitive Impairment and Dementia: A Machine Learning Approach.

BACKGROUND: Efforts to identify important risk factors for cognitive impairment and dementia have to...

Using Machine Learning to Predict Dementia from Neuropsychiatric Symptom and Neuroimaging Data.

BACKGROUND: Machine learning (ML) is a promising technique for patient-specific prediction of mild c...

A Machine Learning Framework for Assessment of Cognitive and Functional Impairments in Alzheimer's Disease: Data Preprocessing and Analysis.

The neuropsychological scores and Functional Activities Questionnaire (FAQ) are significant to measu...

Application and Development of Artificial Intelligence and Intelligent Disease Diagnosis.

With the continuous development of artificial intelligence (AI) technology, big data-supported AI te...

Convolutional Neural Network-based MR Image Analysis for Alzheimer's Disease Classification.

BACKGROUND: In this study, we used a convolutional neural network (CNN) to classify Alzheimer's dise...

Machine Learning Predictive Models Can Improve Efficacy of Clinical Trials for Alzheimer's Disease.

BACKGROUND: The ideal participants for Alzheimer's disease (AD) clinical trials would show cognitive...

Predicting Amyloid-β Levels in Amnestic Mild Cognitive Impairment Using Machine Learning Techniques.

BACKGROUND: Amyloid-β positivity (Aβ+) based on PET imaging is part of the enrollment criteria for m...

A Machine Learning Approach to Identify a Circulating MicroRNA Signature for Alzheimer Disease.

BACKGROUND: Accurate diagnosis of Alzheimer disease (AD) involving less invasive molecular procedure...

Recent Advances on the Semi-Supervised Learning for Long Non-Coding RNA-Protein Interactions Prediction: A Review.

In recent years, more and more evidence indicates that long non-coding RNA (lncRNA) plays a signific...

circDeep: deep learning approach for circular RNA classification from other long non-coding RNA.

MOTIVATION: Over the past two decades, a circular form of RNA (circular RNA), produced through alter...

3D-Deep Learning Based Automatic Diagnosis of Alzheimer's Disease with Joint MMSE Prediction Using Resting-State fMRI.

We performed this research to 1) evaluate a novel deep learning method for the diagnosis of Alzheime...

Fusion of ULS Group Constrained High- and Low-Order Sparse Functional Connectivity Networks for MCI Classification.

Functional connectivity networks, derived from resting-state fMRI data, have been found as effective...

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