Geriatrics

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

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Subcategories: Alzheimer's Disease Medicare
Showing 421-441 of 7,162 articles
Genome-wide methylome modeling via generative AI incorporating long- and short-range interactions.

Using millions of methylation segments, we developed DiffuCpG, a generative artificial intelligence ...

The Role of ChatGPT in osteoporosis management: a comparative analysis with clinical expertise.

UNLABELLED: This study evaluates the role of ChatGPT in osteoporosis management, demonstrating 91% d...

Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated delirium.

This study aimed to develop models for predicting the 30-day mortality of sepsis-associated delirium...

S4-KD: A single step spiking SiamFC+ + for object tracking with knowledge distillation.

Spiking neural networks (SNNs), which transmit information through binary spikes, have the advantage...

Optimization of shunting operation plan in large freight train depot based on DQN algorithm.

Shunting operation plan is the main daily work of the freight train depot, the optimization of shunt...

Knowledge Representation and Management in the Age of Long Covid and Large Language Models: a 2022-2023 Survey.

OBJECTIVES: To select, present, and summarize cutting edge work in the field of Knowledge Representa...

An oral robotic pill reliably and safely delivers teriparatide with high bioavailability in healthy volunteers: A phase 1 study.

AIMS: The incidence of osteoporosis is projected to exceed 70 million people over the age of 65 year...

The Cognivue Amyloid Risk Measure (CARM): A Novel Method to Predict the Presence of Amyloid with Cognivue Clarity.

INTRODUCTION: At the present time, clinical detection of individuals who have amyloid in their brain...

Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies.

Sarcopenia and body composition metrics are strongly associated with patient outcomes. In this study...

Ensemble deep learning for Alzheimer's disease diagnosis using MRI: Integrating features from VGG16, MobileNet, and InceptionResNetV2 models.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloi...

Unsupervised brain MRI tumour segmentation via two-stage image synthesis.

Deep learning shows promise in automated brain tumour segmentation, but it depends on costly expert ...

Design of an Interactive Exercise and Leisure System for the Elderly Integrating Artificial Intelligence and Motion-Sensing Technology.

In response to the global trend of population aging, the issue of providing elderly individuals suit...

The impact of Alzheimer's disease on cortical complexity and its underlying biological mechanisms.

BACKGROUND: Alzheimer's disease (AD) might impact the complexity of cerebral cortex, and the underly...

An isodose-constrained automatic treatment planning strategy using a multicriteria predicted dose rating.

BACKGROUND: Previous knowledge-based planning studies have demonstrated the feasibility of predictin...

A fine-tuned convolutional neural network model for accurate Alzheimer's disease classification.

Alzheimer's disease (AD) is one of the primary causes of dementia in the older population, affecting...

DEMENTIA: A Hybrid Attention-Based Multimodal and Multi-Task Learning Framework With Expert Knowledge for Alzheimer's Disease Assessment From Speech.

The prevalence of Alzheimer's disease (AD) is rising annually, imposing a severe burden on patients ...

TransformDDI: The Transformer-Based Joint Multi-Task Model for End-to-End Drug-Drug Interaction Extraction.

Drug-Drug Interactions (DDI) identification is a part of the drug safety process, that focuses at av...

LGG-NeXt: A Next Generation CNN and Transformer Hybrid Model for the Diagnosis of Alzheimer's Disease Using 2D Structural MRI.

Incurable Alzheimer's disease (AD) plagues many elderly people and families. It is important to accu...

A Novel Hierarchical Cross-Stream Aggregation Neural Network for Semantic Segmentation of 3-D Dental Surface Models.

Accurate teeth delineation on 3-D dental models is essential for individualized orthodontic treatmen...

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