Geriatrics

A cross-sectional study comparing machine learning and logistic regression techniques for predicting osteoporosis in a group at high risk of cardiovascular disease among old adults.

BACKGROUND: Osteoporosis has become a significant public health concern that necessitates the application of appropriate techniques to calculate disease risk. Traditional methods, such as logistic regression,have been widely used to identify risk factors and predict disease probability. However,with the advent of advanced statistics techniques,machine learning models offer promising alternatives f...

Deciphering aging-associated prognosis and heterogeneity in gastric cancer through a machine learning-driven approach.

Gastric cancer (GC) is a prevalent malignancy with a high mortality rate and limited treatment options. Aging significantly contributes to tumor progression, and GC was confirmed as an aging-related heterogeneous disease. This study established an aging-associated index (AAI) using a machine learning-derived gene panel to stratify GC patients. High AAI scores associated with poor prognosis and ind...

F-FDG PET radiomics score construction by automatic machine learning for treatment response prediction in elderly patients with diffuse large B-cell lymphoma: a multicenter study.

PURPOSE: To explore the development and validation of automated machine learning (AutoML) models for F-FDG PET imaging-based radiomics signatures to p...

Development and evaluation of a machine learning model for osteoporosis risk prediction in Korean women.

BACKGROUND: The aim of this study was to develop a machine learning (ML) model for classifying osteoporosis in Korean women based on a large-scale pop...

Fall recognition using a three stream spatio temporal GCN model with adaptive feature aggregation.

The prevention of falls is paramount in modern healthcare, particularly for the elderly, as falls can lead to severe injuries or even fatalities. Addi...

A Systematic Review of Surface Electromyography in Sarcopenia: Muscles Involved, Signal Processing Techniques, Significant Features, and Artificial Intelligence Approaches.

Sarcopenia, affecting between 1-29% of the older population, is characterized by an age-related loss of skeletal muscle mass and function. Reduced mus...

Remote monitoring of Tai Chi balance training interventions in older adults using wearable sensors and machine learning.

Tai Chi, an Asian martial art, is renowned for its health benefits, particularly in promoting healthy aging among older adults, improving balance, and...

Leveraging Extended Windows in End-to-End Deep Learning for Improved Continuous Myoelectric Locomotion Prediction.

Current surface electromyography (sEMG) methods for locomotion mode prediction face limitations in anticipatory capability due to computation delays a...

Mechanisms Tackling Salivary Gland Diseases with Extracellular Vesicle Therapies.

Extracellular vesicles (EVs) are lipid-enclosed particles released from cells, containing lipids, DNA, RNA, metabolites, and cytosolic and cell surfac...

A Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials.

BACKGROUND AND OBJECTIVES: Among the participants of Alzheimer disease (AD) treatment trials, 40% do not show cognitive decline over 80 weeks of follo...

Ensemble network using oblique coronal MRI for Alzheimer's disease diagnosis.

Alzheimer's disease (AD) is a primary degenerative brain disorder commonly found in the elderly, Mild cognitive impairment (MCI) can be considered a t...

Accuracy and quality of ChatGPT-4o and Google Gemini performance on image-based neurosurgery board questions.

Large-language models (LLMs) have shown the capability to effectively answer medical board examination questions. However, their ability to answer ima...

AI Efficiency in Dentistry: Comparing Artificial Intelligence Systems with Human Practitioners in Assessing Several Periodontal Parameters.

Artificial intelligence (AI) is increasingly used in healthcare, including dental and periodontal diagnostics, due to its ability to analyze complex d...

Class balancing diversity multimodal ensemble for Alzheimer's disease diagnosis and early detection.

Alzheimer's disease (AD) poses significant global health challenges due to its increasing prevalence and associated societal costs. Early detection an...

Optimizing heart disease diagnosis with advanced machine learning models: a comparison of predictive performance.

Cardiovascular disease is the leading cause of mortality globally, necessitating precise and prompt predictive instruments to enhance patient outcomes...

Bioinformatics and machine learning approaches to explore key biomarkers in muscle aging linked to adipogenesis.

Adipogenesis is intricately linked to the onset and progression of muscle aging; however, the relevant biomarkers remain unclear. This study sought to...

Risk prediction models for frailty in older adults: A systematic review and critical appraisal.

BACKGROUND: Frailty can lead to increased adverse health outcomes in older adults. Risk prediction models for frailty have benefits in guiding the pre...

AI-based deformable hippocampal mesh reflects hippocampal morphological characteristics in relation to cognition in healthy older adults.

Magnetic resonance imaging (MRI)-derived hippocampus measurements have been associated with different cognitive domains. The knowledge of hippocampal ...

PULSE: A DL-Assisted Physics-Based Approach to the Inverse Problem of Electrocardiography.

This study introduces an innovative approach combining deep-learning techniques with classical physics-based electrocardiographic imaging (ECGI) metho...

Integrating machine learning and a large language model to construct a domain knowledge graph for reducing the risk of fall-from-height accidents.

Fall-from-height (FFH) accidents remain a major source of workplace injuries and fatalities. Fall protection systems (FPS) are critical for preventing...