AIMC Topic: China

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

BMJ open
OBJECTIVE: To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced decision-making and targeted health management in integrat...

Machine learning-based detection of changes in mapping the mangrove forest of the Yangon estuary, Southeast Asia.

Marine environmental research
Mangrove forests are globally acknowledged for stabilizing coastlines, reducing wave energy, and protecting coastal habitats and adjacent land uses from extreme events. However, most regions experience alarming mangrove loss against natural and human...

Factors influencing innovative work behavior among teachers in the higher education sectors in China: The role of work engagement as a mediator and artificial intelligence as a moderator.

Acta psychologica
The modernization of Chinese higher education relies heavily on fostering innovative work behavior (IWB) among university teachers. However, the crucial role of non-intellectual and external factors has often been overlooked, contributing to insuffic...

Sperm metabolomic signatures of asthenozoospermia and teratozoospermia in Chinese reproductive-age men.

Scientific reports
Asthenozoospermia and teratozoospermia are common causes of male infertility. Despite their prevalence, the underlying metabolic mechanisms remain poorly understood. In this study, we conducted targeted metabolomic profiling of sperm samples from 131...

Knowledge, attitudes, and practices of cardiovascular health care personnel regarding coronary CTA and AI-assisted diagnosis: a cross-sectional study.

Journal of global health
BACKGROUND: Artificial intelligence (AI) holds significant promise for medical applications, particularly in coronary computed tomography angiography (CTA). We assessed the knowledge, attitudes, and practices (KAP) of cardiovascular health care perso...

A Bayesian Maximum Entropy Fusion model for enhanced prediction and risk assessment of fluoride and arsenic contamination in groundwater.

Journal of contaminant hydrology
In the central and western regions of Jilin Province, excessive groundwater extraction has resulted in elevated levels of fluoride (F) and arsenic (As) in drinking water. Prolonged exposure to these contaminants is linked to endemic health issues, in...

The value of triglyceride-glucose index-related indices in evaluating migraine: perspectives from multi-centre cross-sectional studies and machine learning models.

Lipids in health and disease
BACKGROUND: This study employed representative data from the U.S. and China to delve into the correlation among migraine prevalence, the triglyceride‒glucose index, a marker of insulin resistance, and the composite indicator of obesity.

Predicting carotid atherosclerosis in latent autoimmune diabetes in adult patients using machine learning models: a retrospective study.

BMC cardiovascular disorders
BACKGROUND: Latent autoimmune diabetes in adults (LADA) is a slowly progressing form of diabetes with autoimmune origins. Patients with LADA are at an elevated risk of developing cardiovascular diseases, including carotid atherosclerosis. While machi...

Enhancing game outcome prediction in the Chinese basketball league through a machine learning framework based on performance data.

Scientific reports
Basketball remains among the most globally popular sports, with its various competitions drawing substantial attention. The analysis and modeling of basketball game data have long been central topics in sports analytics. In recent years, integrating ...

Exploring the complex associations between community public spaces and healthy aging: an explainable analysis using catboost and SHAP.

BMC public health
BACKGROUND: As global aging accelerates, community public spaces (CPS) are increasingly recognized as vital for promoting healthy aging. However, existing research often employs linear analytical methods or focuses on single health dimensions, overlo...