Geriatrics

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

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SVM-LncRNAPro: An SVM-Based Method for Predicting Long Noncoding RNA Promoters.

Long non-coding RNAs (lncRNAs) are closely associated with the regulation of gene expression, whose ...

Artificial Intelligence Methods in Infection Biology Research.

Despite unprecedented achievements, the domain-specific application of artificial intelligence (AI) ...

Unveiling the Immune Landscape of Delirium through Single-Cell RNA Sequencing and Machine Learning: Towards Precision Diagnosis and Therapy.

BACKGROUND: Postoperative delirium (POD) poses significant clinical challenges regarding its diagnos...

A Multi-Label Deep Learning Model for Detailed Classification of Alzheimer's Disease.

BACKGROUND: Accurate diagnosis and classification of Alzheimer's disease (AD) are crucial for effect...

Diagnosis Osteoporosis Risk: Using Machine Learning Algorithms Among Fasa Adults Cohort Study (FACS).

INTRODUCTION: In Iran, the assessment of osteoporosis through tools like dual-energy X-ray absorptio...

Unveiling Long Non-coding RNA Networks from Single-Cell Omics Data Through Artificial Intelligence.

Single-cell omics technologies have revolutionized the study of long non-coding RNAs (lncRNAs), offe...

A Machine Learning Model to Harmonize Volumetric Brain MRI Data for Quantitative Neuroradiologic Assessment of Alzheimer Disease.

Purpose To extend a previously developed machine learning algorithm for harmonizing brain volumetric...

A Dynamic Model for Early Prediction of Alzheimer's Disease by Leveraging Graph Convolutional Networks and Tensor Algebra.

Alzheimer's disease (AD) is a neurocognitive disorder that deteriorates memory and impairs cognitive...

Uncovering Important Diagnostic Features for Alzheimer's, Parkinson's and Other Dementias Using Interpretable Association Mining Methods.

Alzheimer's Disease and Related Dementias (ADRD) afflict almost 7 million people in the USA alone. T...

Biologically Enhanced Machine Learning Model to uncover Novel Gene-Drug Targets for Alzheimer's Disease.

Given the complexity and multifactorial nature of Alzheimer's disease, investigating potential drug-...

DeepTransformer: Node Classification Research of a Deep Graph Network on an Osteoporosis Graph based on GraphTransformer.

BACKGROUND: Osteoporosis (OP) is one of the most common diseases in the elderly population. It is mo...

Mini-mental status examination phenotyping for Alzheimer's disease patients using both structured and narrative electronic health record features.

OBJECTIVE: This study aims to automate the prediction of Mini-Mental State Examination (MMSE) scores...

Integrated Deep Learning Model for the Detection, Segmentation, and Morphologic Analysis of Intracranial Aneurysms Using CT Angiography.

Purpose To develop a deep learning model for the morphologic measurement of unruptured intracranial ...

A Comprehensive Review on Deep Learning Techniques in Alzheimer's Disease Diagnosis.

Alzheimer's Disease (AD) is a serious neurological illness that causes memory loss gradually by dest...

Optimizing Neuroprotective Nano-structured Lipid Carriers for Transdermal Delivery through Artificial Neural Network.

BACKGROUND: Dementia associated with Alzheimer's disease (AD) is a neurological disorder. AD is a pr...

Exploring the Mechanisms of Sanguinarine in the Treatment of Osteoporosis by Integrating Network Pharmacology Analysis and Deep Learning Technology.

BACKGROUND: Sanguinarine (SAN) has been reported to have antioxidant, antiinflammatory, and antimicr...

Dynamic and concordance-assisted learning for risk stratification with application to Alzheimer's disease.

Dynamic prediction models capable of retaining accuracy by evolving over time could play a significa...

Ligand identification in CryoEM and X-ray maps using deep learning.

MOTIVATION: Accurately identifying ligands plays a crucial role in the process of structure-guided d...

Accurate and Efficient Algorithm for Detection of Alzheimer Disability Based on Deep Learning.

BACKGROUND/AIMS: Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that severely ...

segcsvd: A Convolutional Neural Network-Based Tool for Quantifying White Matter Hyperintensities in Heterogeneous Patient Cohorts.

White matter hyperintensities (WMH) of presumed vascular origin are a magnetic resonance imaging (MR...

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