Geriatrics

A deep learning methodology for the automated detection of end-diastolic frames in intravascular ultrasound images.

Coronary luminal dimensions change during the cardiac cycle. However, contemporary volumetric intrav...

Plasma d-glutamate levels for detecting mild cognitive impairment and Alzheimer's disease: Machine learning approaches.

BACKGROUND: d-glutamate, which is involved in N-methyl-d-aspartate receptor modulation, may be assoc...

Machine learning identifies candidates for drug repurposing in Alzheimer's disease.

Clinical trials of novel therapeutics for Alzheimer's Disease (AD) have consumed a large amount of t...

A 3D densely connected convolution neural network with connection-wise attention mechanism for Alzheimer's disease classification.

PURPOSE: Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. In re...

Feasibility of the use of deep learning classification of teat-end condition in Holstein cattle.

Infections with pathogenic bacteria entering the mammary gland through the teat canal are the most c...

A Low-Cost Three-Dimensional DenseNet Neural Network for Alzheimer's Disease Early Discovery.

Alzheimer's disease is the most prevalent dementia among the elderly population. Early detection is ...

A Correlation Analysis between SNPs and ROIs of Alzheimer's Disease Based on Deep Learning.

. At present, the research methods for image genetics of Alzheimer's disease based on machine learni...

Deep learning-based T1-enhanced selection of linear attenuation coefficients (DL-TESLA) for PET/MR attenuation correction in dementia neuroimaging.

PURPOSE: The accuracy of existing PET/MR attenuation correction (AC) has been limited by a lack of c...

Bone strain index as a predictor of further vertebral fracture in osteoporotic women: An artificial intelligence-based analysis.

BACKGROUND: Osteoporosis is an asymptomatic disease of high prevalence and incidence, leading to bon...

Barriers and facilitators to the implementation of social robots for older adults and people with dementia: a scoping review protocol.

BACKGROUND: Psychosocial health issues such as depression and social isolation are an important caus...

Multi-Scale Context-Guided Deep Network for Automated Lesion Segmentation With Endoscopy Images of Gastrointestinal Tract.

Accurate lesion segmentation based on endoscopy images is a fundamental task for the automated diagn...

An anatomical knowledge-based MRI deep learning pipeline for white matter hyperintensity quantification associated with cognitive impairment.

Recent studies have confirmed that white matter hyperintensities (WMHs) accumulated in strategic bra...

Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database.

BACKGROUND: Accurate prognostication is crucial in treatment decisions made for men diagnosed with n...

Large-Scale Modeling of Multispecies Acute Toxicity End Points Using Consensus of Multitask Deep Learning Methods.

Computational methods to predict molecular properties regarding safety and toxicology represent alte...

The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining.

Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serio...

Improved Segmentation of the Intracranial and Ventricular Volumes in Populations with Cerebrovascular Lesions and Atrophy Using 3D CNNs.

Successful segmentation of the total intracranial vault (ICV) and ventricles is of critical importan...

Comprehensive Review of Vision-Based Fall Detection Systems.

Vision-based fall detection systems have experienced fast development over the last years. To determ...

Calibration of the EBT3 Gafchromic Film Using HNN Deep Learning.

To achieve a dose distribution conformal to the target volume while sparing normal tissues, intensit...

A Machine Learning Multi-Class Approach for Fall Detection Systems Based on Wearable Sensors with a Study on Sampling Rates Selection.

Falls are dangerous for the elderly, often causing serious injuries especially when the fallen perso...

A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease.

Alzheimer's disease (AD) is the most common type of dementia. Its diagnosis and progression detectio...

Machine Learning Improves Analysis of Multi-Omics Data in Aging Research and Geroscience.