Geriatrics

AADNet: An End-to-End Deep Learning Model for Auditory Attention Decoding.

Auditory attention decoding (AAD) is the process of identifying the attended speech in a multi-talker environment using brain signals, typically recorded through electroencephalography (EEG). Over the past decade, AAD has undergone continuous development, driven by its promising application in neuro-steered hearing devices. Most AAD algorithms are relying on the increase in neural entrainment to t...

Overcoming Information Sparsity in Metasurfaces for Full-Color Holography via End-to-End Design.

We propose an end-to-end (E2E) system for RGB meta-hologram generation that efficiently determines the optimal material and geometry for target holograms, eliminating the need for exhaustive simulations of every possible meta-atom configuration. A neural network is developed to accurately map the material and structural parameters to the transmission spectra of the single-layered metasurfaces. The...

Deep ensemble learning with transformer models for enhanced Alzheimer's disease detection.

The progression of Alzheimer's disease is relentless, leading to a worsening of mental faculties over time. Currently, there is no remedy for this ill...

MMDental - A multimodal dataset of tooth CBCT images with expert medical records.

In the rapidly evolving field of dental intelligent healthcare, where Artificial Intelligence (AI) plays a pivotal role, the demand for multimodal dat...

Machine learning models for predicting multimorbidity trajectories in middle-aged and elderly adults.

Multimorbidity has emerged as a significant public health issue in the context of global population aging. Predicting and managing the progression of ...

Enhancing automated detection and classification of dementia in individuals with cognitive impairment using artificial intelligence techniques.

Dementia is a degenerative and chronic disorder, increasingly prevalent among older adults, posing significant challenges in providing appropriate car...

Development and Validation of a Nomogram for Predicting Oral Frailty Risk in Elderly Patients With Ischaemic Stroke.

AIM: To develop and validate a risk prediction model for oral frailty in elderly patients with ischaemic stroke.

Validation of The Umbrella Collaboration for Tertiary Evidence Synthesis in Geriatrics: Mixed Methods Study.

BACKGROUND: The synthesis of evidence in health care is essential for informed decision-making and policy development. This study aims to validate The...

Unveiling aging heterogeneities in human dermal fibroblasts via nanosensor chemical cytometry.

Aging heterogeneity in tissue-regenerative cells leads to variable therapeutic outcomes, complicating quality control and clinical predictability. Con...

Speech production as an artificial intelligence-based 'process' measure of cognition sensitive to mild cognitive impairment and Alzheimer's disease.

Process scores in neuropsychological tests add incremental validity for detecting non-normative cognitive aging trajectories. However, process scores...

EEG Signal Analysis for the Classification of Alzheimer's and Frontotemporal Dementia: A Novel Approach Using Artificial Neural Networks and Cross-Entropy Techniques.

Dementia, a neurological disorder, can cause cognitive decline due to damage to the brain. Our study aims to contribute to the development of computer...

Hyper-spherical Optimal Transport for Semantic Alignment in Text-to-3D End-to-end Generation.

Recent CLIP-guided 3D generation methods have achieved promising results but struggle with generating faithful 3D shapes that conform with input text ...

Enhanced particle swarm optimization for feature selection in SVM-based Alzheimer's disease diagnosis.

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder marked by neuronal loss, leading to cognitive and behavioral decline. With the ag...

Gender difference in cross-sectional area and fat infiltration of thigh muscles in the elderly population on MRI: an AI-based analysis.

BACKGROUND: Aging alters musculoskeletal structure and function, affecting muscle mass, composition, and strength, increasing the risk of falls and lo...

Association of dietary quality, biological aging, progression and mortality of cardiovascular-kidney-metabolic syndrome: insights from mediation and machine learning approaches.

BACKGROUND: To investigate the association between the Dietary Inflammatory Index (DII), biological aging, and the staging and mortality of cardiovasc...

Biomimetic Analysis of Neurotransmitters for Disease Diagnosis through Light-Driven Nanozyme Sensor Array and Machine Learning.

Neurological diseases, including Alzheimer's disease, Parkinson's disease, and multiple sclerosis, pose a significant global health challenge due to t...

Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn's disease.

BACKGROUND: Crohn's disease (CD) is a chronic inflammatory bowel disease, with infliximab (IFX) commonly used for treatment. However, no clinically ap...

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China.

OBJECTIVE: To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with...

Early warning and stratification of the elderly cardiopulmonary dysfunction-related diseases: multicentre prospective study protocol.

INTRODUCTION: In China, there is a lack of standardised clinical imaging databases for multidimensional evaluation of cardiopulmonary diseases. To add...

Quantitative CT Imaging in Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous condition characterized by diverse pulmonary and extrapulmonary manifestations....