Geriatrics

Transforming the future of health: building learning health systems across the globe.

Health care has faced disruptions over the past 5 years, including a global pandemic, supply chain interruptions, workforce shifts, and the introduction of new artificial intelligence (AI) tools. Health care organizations continue to leverage the learning health system (LHS) concept to adapt to these challenges through iterative feedback loops. The Future of Health (FOH), an international communit...

Large-scale plasma proteomic profiling unveils diagnostic biomarkers and pathways for Alzheimer's disease.

Proteomic studies have been instrumental in identifying brain, cerebrospinal fluid and plasma proteins associated with Alzheimer's disease (AD). Here, we comprehensively examined 6,905 aptamers corresponding to 6,106 unique proteins in plasma in more than 3,300 well-characterized individuals to identify new proteins, pathways and predictive models for AD. We identified 416 proteins (294 new) assoc...

Exploring the diagnostic potential of EEG theta power and interhemispheric correlation of temporal lobe activities in Alzheimer's Disease through random forest analysis.

BACKGROUND: Considering the prevalence of Alzheimer's Disease (AD) among the aging population and the limited means of treatment, early detection emer...

Fully Hyperbolic Neural Networks: A Novel Approach to Studying Aging Trajectories.

Characterizing age-related alterations in brain networks is crucial for understanding aging trajectories and identifying deviations indicative of neur...

Enhancing osteoporosis risk prediction using machine learning: A holistic approach integrating biomarkers and clinical data.

Osteoporosis (OP) affects approximately 18 % of the global population, with osteoporosis-associated fractures impacting up to 37 million people annual...

GeneDX-PBMC: An adversarial autoencoder framework for unlocking Alzheimer's disease biomarkers using blood single-cell RNA sequencing data.

OBJECTIVE: To identify blood-based biomarkers and therapeutic targets for Alzheimer's disease (AD) by leveraging single-cell RNA sequencing (scRNA-seq...

EB-YOLO:An efficient and lightweight blood cell detector based on the YOLO algorithm.

Blood cell detection is an important part of medical diagnosis. Object detection is trending for blood cell analysis, with research focusing on high-p...

Applying an Agile Science Roadmap to Integrate and Evaluate Ethical Frameworks Throughout the Lifecycle and Use of Artificial Intelligence Tools in the Intensive Care Unit.

This article summarizes existing ethical frameworks for healthcare artificial intelligence (AI) and ambient sensing technology, such as computer visio...

Detection of emergency department patients at risk of dementia through artificial intelligence.

INTRODUCTION: The study aimed to develop and validate the Emergency Department Dementia Algorithm (EDDA) to detect dementia among older adults (65+) a...

Comparison of Sarcopenia Assessment in Liver Transplant Recipients by Computed Tomography Freehand Region-of-Interest versus an Automated Deep Learning System.

INTRODUCTION: Sarcopenia, or the loss of muscle quality and quantity, has been associated with poor clinical outcomes in liver transplantation such as...

Radiomics of PET Using Neural Networks for Prediction of Alzheimer's Disease Diagnosis.

Positron emission tomography (PET) imaging technology is widely used for diagnosing Alzheimer's disease (AD) in people with dementia. Although various...

Network Occlusion Sensitivity Analysis Identifies Regional Contributions to Brain Age Prediction.

Deep learning frameworks utilizing convolutional neural networks (CNNs) have frequently been used for brain age prediction and have achieved outstandi...

Enhancing wisdom teeth detection in panoramic radiographs using multi-channel convolutional neural network with clinical knowledge.

This study presents a novel artificial intelligence approach for detecting wisdom teeth in panoramic radiographs using a multi-channel convolutional n...

Sharing patient technology preferences with care networks: Stakeholders' views of the "Let's Talk Tech" decision aid for dementia care.

BackgroundLet's Talk Tech (LTT) is a self-administered web intervention for people with memory loss and their care partners that supports decision-mak...

Multimodal fusion architectures for Alzheimer's disease diagnosis: An experimental study.

OBJECTIVE: In the attempt of early diagnosis of Alzheimer's Disease, varying forms of medical records of multiple modalities are gathered to seize the...

Human Fall Detection using Transfer Learning-based 3D CNN

Unintentional or accidental falls are one of the significant health issues in senior persons. The population of senior persons is increasing steadil...

DuAL-Net: A Hybrid Framework for Alzheimer's Disease Prediction from Whole-Genome Sequencing via Local SNP Windows and Global Annotations

Alzheimer's disease (AD) dementia is the most common form of dementia. With the emergence of disease-modifying therapies, predicting disease risk be...

Uncertainty-Aware Genomic Classification of Alzheimer's Disease: A Transformer-Based Ensemble Approach with Monte Carlo Dropout

INTRODUCTION: Alzheimer's disease (AD) is genetically complex, complicating robust classification from genomic data. METHODS: We developed a transfo...

LoHoVLA: A Unified Vision-Language-Action Model for Long-Horizon Embodied Tasks

Real-world embodied agents face long-horizon tasks, characterized by high-level goals demanding multi-step solutions beyond single actions. Successf...

Deep-learning based multi-modal models for brain age, cognition and amyloid pathology prediction.

BACKGROUND: Magnetic resonance imaging (MRI), combined with artificial intelligence techniques, has improved our understanding of brain structural cha...