Geriatrics

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

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Subcategories: Alzheimer's Disease Medicare
Showing 778-798 of 7,204 articles
Age-Related Cognitive and Volumetric Changes in the Brain of African Grasscutter ( (Temminck, 1827)).

The African grasscutter (AGC) () is the second largest rodent in sub-Saharan Africa. It is bred for ...

A machine learning approach for identifying anatomical biomarkers of early mild cognitive impairment.

BACKGROUND: Alzheimer's Disease (AD) poses a major challenge as a neurodegenerative disorder, and ea...

Random survival forest model for early prediction of Alzheimer's disease conversion in early and late Mild cognitive impairment stages.

With a clinical trial failure rate of 99.6% for Alzheimer's Disease (AD), early diagnosis is critica...

Time-Frequency functional connectivity alterations in Alzheimer's disease and frontotemporal dementia: An EEG analysis using machine learning.

OBJECTIVE: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are prevalent neurodegenerativ...

ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists' intentions.

Using Deep Learning in computer-aided diagnosis systems has been of great interest due to its impres...

Blood Biomarker Signatures for Slow Gait Speed in Older Adults: An Explainable Machine Learning Approach.

Maintaining physical function is crucial for independent living in older adults, with gait speed bei...

Synthetic data analysis for early detection of Alzheimer progression through machine learning algorithms.

Alzheimer's disease (AD) is a serious neurodegenerative disorder that causes incurable and irreversi...

Predicting intra-abdominal candidiasis in elderly septic patients using machine learning based on lymphocyte subtyping: a prospective cohort study.

OBJECTIVE: Intra-abdominal candidiasis (IAC) is difficult to predict in elderly septic patients with...

Early detection of Alzheimer's disease in structural and functional MRI.

OBJECTIVES: To implement state-of-the-art deep learning architectures such as Deep-Residual-U-Net an...

Early Detection of Dementia in Populations With Type 2 Diabetes: Predictive Analytics Using Machine Learning Approach.

BACKGROUND: The possible association between diabetes mellitus and dementia has raised concerns, giv...

Robust long-tailed recognition with distribution-aware adversarial example generation.

Confronting adversarial attacks and data imbalances, attaining adversarial robustness under long-tai...

End-to-end deep learning patient level classification of affected territory of ischemic stroke patients in DW-MRI.

PURPOSE: To develop an end-to-end DL model for automated classification of affected territory in DWI...

An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.

Protein-protein interactions (PPIs) are essential to understanding cellular mechanisms, signaling ne...

CTsynther: Contrastive Transformer Model for End-to-End Retrosynthesis Prediction.

Retrosynthesis prediction is a fundamental problem in organic chemistry and drug synthesis. We propo...

A neural network integrated mathematical model to analyze the impact of nutritional status on cognitive development of child.

Cognitive development is a crucial developmental aspect of children. It is a concise field of study ...

Natural compounds for Alzheimer's prevention and treatment: Integrating SELFormer-based computational screening with experimental validation.

BACKGROUND: This study aimed to develop and apply a novel computational pipeline combining SELFormer...

Automated landmark-based cat facial analysis and its applications.

Facial landmarks, widely studied in human affective computing, are beginning to gain interest in the...

Machine learning based algorithms for virtual early detection and screening of neurodegenerative and neurocognitive disorders: a systematic-review.

BACKGROUND AND AIM: Neurodegenerative disorders (e.g., Alzheimer's, Parkinson's) lead to neuronal lo...

Fatal fall from a height: is it possible to apply artificial intelligence techniques for height estimation?

Fall from a height trauma is characterized by a multiplicity of injuries, related to multiple factor...

A multi-view learning approach with diffusion model to synthesize FDG PET from MRI T1WI for diagnosis of Alzheimer's disease.

INTRODUCTION: This study presents a novel multi-view learning approach for machine learning (ML)-bas...

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