Geriatrics

The association between sports social capital and cognitive health: A longitudinal study of middle-aged and elderly adults in China.

This study examines the association between sports social capital and cognitive health in middle-age...

Biological age prediction using a DNN model based on pathways of steroidogenesis.

Aging involves the progressive accumulation of cellular damage, leading to systemic decline and age-...

AmIActive (AIA): A Large-scale QSAR Based Target Fishing and Polypharmacology Predictive Web Tool.

Here, we introduce AmIActive (AIA), a QSAR-based web tool for biological activity prediction and tar...

Automated Fast Prediction of Bone Mineral Density From Low-dose Computed Tomography.

BACKGROUND: Low-dose chest CT (LDCT) is commonly employed for the early screening of lung cancer. Ho...

Real-Time Acoustic Scene Recognition for Elderly Daily Routines Using Edge-Based Deep Learning.

The demand for intelligent monitoring systems tailored to elderly living environments is rapidly inc...

Neuropsychological tests and machine learning: identifying predictors of MCI and dementia progression.

BACKGROUND: Early prediction of progression in dementia is of major importance for providing patient...

Development of a visualized risk prediction system for sarcopenia in older adults using machine learning: a cohort study based on CHARLS.

INTRODUCTION: The older adult are at high risk of sarcopenia, making early identification and scient...

Applying machine learning to predict bowel preparation adequacy in elderly patients for colonoscopy: development and validation of a web-based prediction tool.

BACKGROUND: Adequate bowel preparation is crucial for effective colonoscopy, especially in elderly p...

PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach.

OBJECTIVES: Osteoporosis, prevalent among the elderly population, is primarily diagnosed through bon...

Can some algorithms of machine learning identify osteoporosis patients after training and testing some clinical information about patients?

OBJECTIVE: This study was designed to establish a diagnostic model for osteoporosis by collecting cl...

Develop and validate machine learning models to predict the risk of depressive symptoms in older adults with cognitive impairment.

BACKGROUND: Cognitive impairment and depressive symptoms are prevalent and closely interrelated ment...

A comprehensive interpretable machine learning framework for mild cognitive impairment and Alzheimer's disease diagnosis.

An interpretable machine learning (ML) framework is introduced to enhance the diagnosis of Mild Cogn...

Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand.

This study aims to construct a prediction model for the demand for medical and daily care services o...

Using statistical modelling and machine learning in detecting bone properties: A systematic review protocol.

INTRODUCTION: Osteoporosis, a common condition characterised by decreased bone mass and microarchite...

Dementia Overdiagnosis in Younger, Higher Educated Individuals Based on MMSE Alone: Analysis Using Deep Learning Technology.

BACKGROUND: Dementia is a multifaceted disorder that affects cognitive function, necessitating accur...

Interpretable machine learning model for predicting depression in middle-aged and elderly Chinese arthritis patients: A nationwide prospective cohort study.

Transcriptome analysis reveals the potential role of neural factor EN1 for long-terms survival in estrogen receptor-independent breast cancer.

Breast cancer patients with estrogen receptor-negative (ERneg) status, encompassing triple negative ...

Machine learning to detect Alzheimer's disease with data on drugs and diagnoses.

BACKGROUND: Integrating machine learning with medical records offers potential for early detection o...

Comparison of Deep Learning and Traditional Machine Learning Models for Predicting Mild Cognitive Impairment Using Plasma Proteomic Biomarkers.

Mild cognitive impairment (MCI) is a clinical condition characterized by a decline in cognitive abil...

AI-Driven decision-making for personalized elderly care: a fuzzy MCDM-based framework for enhancing treatment recommendations.

BACKGROUND: Global healthcare systems face enormous challenges due to the ageing population, demandi...

MCNEL: A multi-scale convolutional network and ensemble learning for Alzheimer's disease diagnosis.

BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) significantly threatens community well-being and ...