Geriatrics

BPEN: Brain Posterior Evidential Network for trustworthy brain imaging analysis.

The application of deep learning techniques to analyze brain functional magnetic resonance imaging (fMRI) data has led to significant advancements in identifying prospective biomarkers associated with various clinical phenotypes and neurological conditions. Despite these achievements, the aspect of prediction uncertainty has been relatively underexplored in brain fMRI data analysis. Accurate uncer...

Effective Alzheimer's disease detection using enhanced Xception blending with snapshot ensemble.

Alzheimer's disease (AD), a prevalent neurodegenerative disorder, leads to progressive dementia, which impairs decision-making, problem-solving, and communication. While there is no cure, early detection can facilitate treatments to slow its progression. Deep learning (DL) significantly enhances AD detection by analyzing brain imaging data to identify early biomarkers, improving diagnostic accurac...

Insights to aging prediction with AI based epigenetic clocks.

Over the past century, human lifespan has increased remarkably, yet the inevitability of aging persists. The disparity between biological age, which r...

Graph Convolutional Network for AD and MCI Diagnosis Utilizing Peripheral DNA Methylation: Réseau de neurones en graphes pour le diagnostic de la MA et du TCL à l'aide de la méthylation de l'ADN périphérique.

OBJECTIVE: Blood DNA methylation (DNAm) alterations have been widely reported in the onset and progression of mild cognitive impairment (MCI) and Alzh...

Identification and cognitive function prediction of Alzheimer's disease based on multivariate pattern analysis of hippocampal volumes.

BACKGROUND: Alzheimer's disease (AD) is strongly associated with slowly progressive hippocampal atrophy. Elucidating the relationships between local m...

Social Robots and Sensors for Enhanced Aging at Home: Mixed Methods Study With a Focus on Mobility and Socioeconomic Factors.

BACKGROUND: Population aging affects society, with a profound impact on daily activities for those of a low socioeconomic status and with motor impair...

Machine learning based on event-related oscillations of working memory differentiates between preclinical Alzheimer's disease and normal aging.

OBJECTIVE: To apply machine learning approaches on EEG event-related oscillations (ERO) to discriminate preclinical Alzheimer's disease (AD) from age-...

Identifying shared diagnostic genes and mechanisms in vascular dementia and Alzheimer's disease via bioinformatics and machine learning.

BACKGROUND: Alzheimer's disease (AD) and vascular dementia (VaD) share overlapping pathophysiological characteristics, yet comparative genetic studies...

The Pivotal Role of Baseline LDCT for Lung Cancer Screening in the Era of Artificial Intelligence.

In this narrative review, we address the ongoing challenges of lung cancer (LC) screening using chest low-dose computerized tomography (LDCT) and expl...

Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK.

INTRODUCTION: Artificial Intelligence (AI) has the potential to transform medical imaging and radiotherapy; both fields where radiographers' use of AI...

Multi-scale multimodal deep learning framework for Alzheimer's disease diagnosis.

Multimodal neuroimaging data, including magnetic resonance imaging (MRI) and positron emission tomography (PET), provides complementary information ab...

Establishing a machine learning dementia progression prediction model with multiple integrated data.

OBJECTIVE: Dementia is a significant medical and social issue in most developed countries. Practical tools for predicting the progression of degenerat...

Dynamic Tracking and Real-Time Fall Detection Based on Intelligent Image Analysis with Convolutional Neural Network.

As many countries face rapid population aging, the supply of manpower for caregiving falls far short of the increasing demand for care. Therefore, if ...

Deep multiple instance learning on heterogeneous graph for drug-disease association prediction.

Drug repositioning offers promising prospects for accelerating drug discovery by identifying potential drug-disease associations (DDAs) for existing d...

Comparison of machine learning methods for Predicting 3-Year survival in elderly esophageal squamous cancer patients based on oxidative stress.

BACKGROUND: Oxidative stress process plays a key role in aging and cancer; however, currently, there is paucity of machine-learning model studies inve...

Moral enhancement and cheapened achievement: Psychedelics, virtual reality and AI.

A prominent critique of cognitive or athletic enhancement claims that certain performance-improving drugs or technologies may 'cheapen' resulting achi...

Artificial intelligence meets the world experts; updates and novel therapies in autoimmunity - The 14th international congress on autoimmunity 2024 (AUTO14), Ljubljana.

The bi-annual international congress on autoimmunity is a huge opportunity for the medical community to discuss the latest updates in the field. Durin...

A Multi-task learning U-Net model for end-to-end HEp-2 cell image analysis.

Antinuclear Antibody (ANA) testing is pivotal to help diagnose patients with a suspected autoimmune disease. The Indirect Immunofluorescence (IIF) mic...

Comprehensive review of dysphagia and technological advances in dysphagia food.

As the global population ages, dysphagia is becoming increasingly common among the elderly, posing serious risks such as choking, aspiration pneumonia...

Multiclass classification of Alzheimer's disease prodromal stages using sequential feature embeddings and regularized multikernel support vector machine.

The detection of patients in the cognitive normal (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD) stages of neurodegeneration is c...