Geriatrics

Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction.

Accurate traffic flow prediction is vital for intelligent transportation systems but presents significant challenges. Existing methods, however, have the following limitations: (1) insufficient exploration of interactions across different temporal scales, which restricts effective future flow prediction; (2) reliance on predefined graph structures in graph neural networks, making it challenging to...

Multivariate multi-horizon time-series forecasting for real-time patient monitoring based on cascaded fine tuning of attention-based models.

The real-time forecasting of critical physiological indicators in intensive care units (ICUs) is essential for early intervention and clinical decision support. This study introduces a novel framework, StreamHealth Multi-Horizon AI, which has been designed to perform multivariate, multi-horizon time-series forecasting for vital signs, specifically for a person's blood oxygen saturation level (SpO2...

Detecting label noise in longitudinal Alzheimer's data with explainable artificial intelligence.

Reliable classification of cognitive states in longitudinal Alzheimer's Disease (AD) studies is critical for early diagnosis and intervention. However...

Machine learning is changing osteoporosis detection: an integrative review.

Machine learning drives osteoporosis detection and screening with higher clinical accuracy and accessibility than traditional osteoporosis screening t...

A cross population study of retinal aging biomarkers with longitudinal pre-training and label distribution learning.

Retinal age has emerged as a promising biomarker of aging, offering a non-invasive and accessible assessment tool. We developed a deep learning model ...

Updates on inherited arrhythmia syndromes (Brugada syndrome, long QT syndrome, CPVT, ARVC).

The inherited arrhythmia (IA) syndromes are a group of rare and complex conditions that may predispose individuals to ventricular arrhythmias and sudd...

Early Alzheimer's Detection Through Voice Analysis: Harnessing Locally Deployable LLMs via , a privacy-preserving diagnostic system.

Diagnosing Alzheimer's Disease (AD) early and cost-effectively is crucial. Recent advancements in Large Language Models (LLMs) like ChatGPT have made ...

Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques.

The rapid decline of kidney function in middle-aged and elderly people has become an increasingly serious public health problem. Machine learning (ML)...

Association of urinary metal elements with sarcopenia and glucose metabolism abnormalities: Insights from NHANES data using machine learning approaches.

BACKGROUND: Sarcopenia, a condition marked by the decline of skeletal muscle mass and function, is prevalent in the elderly and closely linked to abno...

AI-delirium guard: Predictive modeling of postoperative delirium in elderly surgical patients.

INTRODUCTION: In older patients, postoperative delirium (POD) is a major complication that can result in greater morbidity, longer hospital stays, and...

Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China.

BACKGROUND: Cardiovascular-Kidney-Metabolic (CKM) syndrome is a systemic disease characterized by pathophysiological interactions between the cardiova...

Dynamically weighted graph neural network for detection of early mild cognitive impairment.

Alzheimer's disease (AD) is a prevalent neurodegenerative disease that primarily affects the elderly population. The early detection of mild cognitive...

Automated Classification of Cervical Spinal Stenosis Using Deep Learning on Computed Tomography Scans.

STUDY DESIGN: Retrospective study. OBJECTIVE: To develop and validate a computed tomography-based deep learning (DL) model for diagnosing cervical spi...

Social bonding between humans, animals, and robots: Dogs outperform AIBOs, their robotic replicas, as social companions.

In the evolving landscape of technology, robots have emerged as social companions, prompting an investigation into social bonding between humans and r...

A machine learning-based prediction model for sepsis-associated delirium in intensive care unit patients with sepsis-associated acute kidney injury.

Sepsis-associated acute kidney injury (SA-AKI) patients in the ICU often suffer from sepsis-associated delirium (SAD), which is linked to unfavorable ...

Development of a neural network-based risk prediction model for mild cognitive impairment in older adults with functional disability.

BACKGROUND: Mild Cognitive Impairment (MCI) is a critical transitional stage between normal aging and Alzheimer's disease, and its early identificatio...

Role of astroglia and microglia in Alzheimer's disease and multiple therapeutic interventions.

Alzheimer's disease (AD) is characterized by deposition of amyloid-β (Aβ) and neurofibrillary tangles (NFTs) formed by aggregates of hyperphosphorylat...

Geographical distribution disparities and prediction of health satisfaction among middle-aged and elderly adults in China: An analysis based on national data.

BACKGROUND: Health satisfaction among middle-aged and elderly adults has become a critical public health concern in China's aging society. Understandi...

Using machine learning to identify predictors of self-perceptions of aging among older adults in England.

OBJECTIVES: This study aimed to identify the strongest predictors of self-perceptions of aging (SPA) from an extensive set of 55 variables, including ...

Selection, visualization, and explanation of deep features from resting-state fMRI for Alzheimer's disease diagnosis.

Despite the remarkable achievements of deep learning networks in analyzing neuroimaging data for various tasks linked to brain functions and disorders...