Geriatrics

Ensemble-learning approach improves fracture prediction using genomic and phenotypic data.

UNLABELLED: This study presents an innovative ensemble machine learning model integrating genomic an...

Multitask Deep Learning Models of Combined Industrial Absorption, Distribution, Metabolism, and Excretion Datasets to Improve Generalization.

The optimization of absorption, distribution, metabolism, and excretion (ADME) profiles of compounds...

An explainable machine learning-based prediction model for sarcopenia in elderly Chinese people with knee osteoarthritis.

BACKGROUND: Sarcopenia is an age-related progressive skeletal muscle disease that leads to loss of m...

Alzheimer's disease prediction using 3D-CNNs: Intelligent processing of neuroimaging data.

Alzheimer's disease (AD) is a severe neurological illness that demolishes memory and brain functioni...

A comprehensive approach to anticipating the progression of mild cognitive impairment.

The immersive experience provided by our approach empowers researchers with an intuitive exploration...

Mechanical Structure Design and Motion Simulation Analysis of a Lower Limb Exoskeleton Rehabilitation Robot Based on Human-Machine Integration.

Population aging is an inevitable trend in contemporary society, and the application of technologies...

Deep learning-based classification of dementia using image representation of subcortical signals.

BACKGROUND: Dementia is a neurological syndrome marked by cognitive decline. Alzheimer's disease (AD...

A Lightweight Deep Convolutional Neural Network Extracting Local and Global Contextual Features for the Classification of Alzheimer's Disease Using Structural MRI.

Recent advancements in the classification of Alzheimer's disease have leveraged the automatic featur...

Learning Consistent Semantic Representation for Chest X-ray via Anatomical Localization in Self-Supervised Pre-Training.

Despite the similar global structures in Chest X-ray (CXR) images, the same anatomy exhibits varying...

Cold storage surpasses the impact of biological age and donor characteristics on red blood cell morphology classified by deep machine learning.

Assessment of the morphology of red blood cells (RBCs) can improve clinical benefits following blood...

Machine Learning-Based Prediction of Delirium and Risk Factor Identification in Intensive Care Unit Patients With Burns: Retrospective Observational Study.

BACKGROUND: The incidence of delirium in patients with burns receiving treatment in the intensive ca...

Enhancing diagnosis prediction with adaptive disease representation learning.

Diagnosis prediction predicts which diseases a patient is most likely to suffer from in the future b...

Differential effects of robot's touch on perceived emotions and the feeling of Kawaii in adults and seniors.

Using social robots is a promising approach for supporting senior citizens in the context of super-a...

Prediction of zinc, cadmium, and arsenic in european soils using multi-end machine learning models.

Heavy metal contamination in soil is a major environmental and public health concern, especially in ...

Applying machine learning to high-dimensional proteomics datasets for the identification of Alzheimer's disease biomarkers.

PURPOSE: This study explores the application of machine learning to high-dimensional proteomics data...

Corrigendum to "A case for the use of deep learning algorithms for individual and population level assessments of mental health disorders: Predicting depression among China's elderly" [J. Affect. Disord. Volume 369, 15 January 2025, Pages 329-337].

Development and multi-center cross-setting validation of an explainable prediction model for sarcopenic obesity: a machine learning approach based on readily available clinical features.

OBJECTIVES: Sarcopenic obesity (SO), characterized by the coexistence of obesity and sarcopenia, is ...

Enhancement of long-horizon task planning via active and passive modification in large language models.

This study proposes a method for generating complex and long-horizon off-line task plans using large...

Enhancing Slip, Trip, and Fall Prevention: Real-World Near-Fall Detection with Advanced Machine Learning Technique.

Slips, trips, and falls (STFs) are a major occupational hazard that contributes significantly to wor...

Therapeutic Mechanisms of Medicine Food Homology Plants in Alzheimer's Disease: Insights from Network Pharmacology, Machine Learning, and Molecular Docking.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by a gradual decl...

Machine Learning Methods for Classifying Multiple Sclerosis and Alzheimer's Disease Using Genomic Data.

Complex diseases pose challenges in prediction due to their multifactorial and polygenic nature. Thi...