Geriatrics

Utilisation of Machine Learning Approaches Improves RNA-Seq Transcriptome Analyses in Alzheimer's Disease Brain.

UNLABELLED: Alzheimer’s disease (AD) is a neurodegenerative disorder that progressively deteriorates a person’s memory, as well as their ability to think and move. It has been reported to be the most common cause of dementia. Alterations in gene expression have been increasingly recognised as key contributors to the onset and progression of AD, driving interest in transcriptomic approaches to bett...

Increasing engagement with cognitive-behavioral therapy (CBT) using generative AI: a randomized controlled trial (RCT).

BACKGROUND: Shortages in mental healthcare lead to long periods of inadequate support for many patients. While digital interventions offer a scalable solution to this unmet clinical need, patient engagement remains a key challenge. Generative artificial intelligence (genAI) presents an opportunity to deliver highly engaging, personalized mental health treatment at scale. METHODS: In a pre-register...

Co-occurrence patterns and related risk factors of dementia and Parkinson's disease among older adults across 204 countries and territories: a spatial correspondence and systematic analysis.

BACKGROUND: Dementia and Parkinson's disease (PD) are among the most prevalent neurological disorders globally. Most previous research has focused on ...

Investigating the molecular mechanisms of glutamine metabolism and mitochondria-related biomarkers in Alzheimer's disease through transcriptomics and experimental validation.

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder. This study aims to identify biomarkers associated with glutamine metab...

The balance between artificial and human intelligence in clinical practice.

INTRODUCTION: Artificial intelligence (AI) is becoming increasingly integrated into clinical care in hand surgery. Its applications extend across diag...

Accurate learning of long-range interatomic potentials by coupling Cartesian atomic cluster expansion and sum-of-Gaussians neural networks.

Accurately capturing long-range interactions is critical for molecular dynamics simulations based on machine learning interatomic potentials. We recen...

Association between cognitive status and structural brain changes in Alzheimer's disease: Clinical implication of lightweight deep learning-aided diagnosis.

BACKGROUND: The complex brain changes involved in Alzheimer's disease (AD) development constitute a high-dimensional nonlinear feature space where dee...

Can OMFS experts distinguish AI from human manuscripts? A double-blind evaluation using ChatGPT-4.

OBJECTIVE: As generative AI tools like ChatGPT-4 gain traction in academic writing, questions arise regarding their credibility, scientific depth, and...

Identifying endoplasmic reticulum stress-related key genes of vascular dementia using bioinformatics and biological experiments.

Vascular dementia (VaD) is the second most common type of dementia, yet its pathogenesis is not fully understood, and effective diagnostic and therape...

Exploring the molecular intersections of osteoporosis and sarcopenia: An integrated bioinformatics and experimental validation.

BACKGROUND: Osteoporosis and sarcopenia are age-related degenerative diseases that frequently co-occur in the older adults, yet their shared molecular...

Evaluating a negotiation training program for family caregivers of older people using a Multiphase Optimization Strategy (MOST) design and protocol.

UNLABELLED: Traditional clinical trial designs such as the isolated two-arm randomized controlled trial (RCT) do not offer robust solutions for evalua...

A two-stage active cleaning strategy for long-tail label noise.

Long-tailed data is ubiquitous in real-world applications, posing significant challenges due to imbalanced class distribution and high levels of label...

A causal bidirectional selective state space model for imaging genetics in neurodegenerative diseases.

Brain imaging genetics aims to uncover the pathological mechanisms and improve the diagnosis of brain diseases, particularly neurodegenerative disorde...

Utilizing artificial intelligence for the diagnosis of ocular surface squamous neoplasia with ultrasound biomicroscopy images.

PURPOSE: This study aims to develop an artificial intelligence (AI) model to assist ophthalmologists in distinguishing ocular surface squamous neoplas...

Predicting cardiovascular diseases using imbalanced data: An XGBoost-based analysis of the 2022 BRFSS dataset.

BACKGROUND: Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, arising from complex interactions among demographic, clini...

An Ensemble Learning Artificial Intelligence Model for Alzheimer's Disease Detection Using OCT.

PURPOSE: There has been significant progress in detecting Alzheimer's disease (AD) using retinal imaging. We developed an ensemble learning-based deep...

A multi-target therapeutic framework for Alzheimer's disease: an integrative mechanistic review.

BACKGROUND: Alzheimer's disease (AD) is increasingly recognized as a multifactorial network disorder in which amyloid and tau pathology interact with ...

FGA Serves as a Potential Diagnostic Marker and Therapeutic Target for Elderly Acute Kidney Injury.

To identify potential biomarkers and explore the underlying mechanisms of elderly acute kidney injury (e-AKI), we performed integrative plasma proteom...

Hippocampus-centered structural covariance network reorganization in Alzheimer's disease: An individualized graph-based biomarker validated by machine learning.

Alzheimer's disease (AD) is characterized by progressive brain network disintegration, yet quantifying this process at an individual level remains cha...

Interpretable machine learning-based prediction of liver metastasis risk in elderly patients with small cell lung Cancer: A study based on the SEER database and external validation in a Chinese cohort.

PURPOSE: Small cell lung cancer (SCLC) is a highly aggressive malignancy with a high incidence of liver metastases, particularly among elderly patient...