Geriatrics

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

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Subcategories: Alzheimer's Disease Medicare
Showing 3004-3024 of 7,288 articles
Identification of 170 New Long Noncoding RNAs in .

Long noncoding RNAs (lncRNAs) are transcripts generally longer than 200 nucleotides with no or poor ...

Unsupervised Machine Learning to Identify High Likelihood of Dementia in Population-Based Surveys: Development and Validation Study.

BACKGROUND: Dementia is increasing in prevalence worldwide, yet frequently remains undiagnosed, espe...

RACE-Net: A Recurrent Neural Network for Biomedical Image Segmentation.

The level set based deformable models (LDM) are commonly used for medical image segmentation. Howeve...

HECIL: A Hybrid Error Correction Algorithm for Long Reads with Iterative Learning.

Second-generation DNA sequencing techniques generate short reads that can result in fragmented genom...

An end to end Deep Neural Network for iris segmentation in unconstrained scenarios.

With the increasing imaging and processing capabilities of today's mobile devices, user authenticati...

Early anomaly detection in smart home: A causal association rule-based approach.

As the world's population grows older, an increasing number of people are facing health issues. For ...

Real-time apnea-hypopnea event detection during sleep by convolutional neural networks.

Sleep apnea-hypopnea event detection has been widely studied using various biosignals and algorithms...

Prediction of Surface Roughness considering Cutting Parameters and Humidity Condition in End Milling of Polyamide Materials.

To know the impact of processing parameters of PA6G under different humidity conditions is important...

A Discrete Multiobjective Particle Swarm Optimizer for Automated Assembly of Parallel Cognitive Diagnosis Tests.

Parallel test assembly has long been an important yet challenging topic in educational assessment. C...

Altered Micro-RNA Regulation and Neuroprotection Activity of in Alzheimer's Disease Model.

BACKGROUND: Amyloid-β peptide (Aβ) is involved in the formation of senile plaques in Alzheimer's dis...

Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease.

Graphs are widely used as a natural framework that captures interactions between individual elements...

The effect of a wearable soft-robotic glove on motor function and functional performance of older adults.

Reduced grip strength, resulting in difficulties in performing daily activities, is a common problem...

Annotating Diseases Using Human Phenotype Ontology Improves Prediction of Disease-Associated Long Non-coding RNAs.

Recently, many long non-coding RNAs (lncRNAs) have been identified and their biological function has...

Integrating spatial-anatomical regularization and structure sparsity into SVM: Improving interpretation of Alzheimer's disease classification.

In recent years, machine learning approaches have been successfully applied to the field of neuroima...

Sarcopenia: Beyond Muscle Atrophy and into the New Frontiers of Opportunistic Imaging, Precision Medicine, and Machine Learning.

As populations continue to age worldwide, the impact of sarcopenia on public health will continue to...

Factors associated with dementia in elderly.

We analyzed the factors associated with dementia in the elderly attended at a memory outpatient clin...

A machine learning model with human cognitive biases capable of learning from small and biased datasets.

Human learners can generalize a new concept from a small number of samples. In contrast, conventiona...

Machine learning identifies signatures of host adaptation in the bacterial pathogen Salmonella enterica.

Emerging pathogens are a major threat to public health, however understanding how pathogens adapt to...

Unobtrusive Activity Recognition of Elderly People Living Alone Using Anonymous Binary Sensors and DCNN.

Elderly population (over the age of 60) is predicted to be 1.2 billion by 2025. Most of the elderly ...

Identification of Alzheimer's disease and mild cognitive impairment using multimodal sparse hierarchical extreme learning machine.

Different modalities such as structural MRI, FDG-PET, and CSF have complementary information, which ...

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