AIMC Topic: China

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Assist me or replace me? Uncovering the influence of AI awareness on employees' counterproductive work behaviors.

Frontiers in public health
OBJECTIVE: Drawing on the conservation of resources theory (COR), the research aims to reveal the influence of artificial intelligence (AI) awareness on employees' mental health and behaviors, particularly examining whether and how employees' AI awar...

Quantification of uncertainty in short-term tropospheric column density risks for a wide range of carbon monoxide.

Journal of environmental management
The short-term risks associated with atmospheric trace gases, particularly carbon monoxide (CO), are critical for ecological security and human health. Traditional statistical methods, which still dominate the assessment of these risks, limit the pot...

Synergistic pathways for health investment and economic development in China: a fuzzy-set qualitative comparative analysis.

Frontiers in public health
BACKGROUND: System coordination is an effective way to achieve high-quality development, and the debate on the interaction between health investment and economic development is still ongoing. To strengthen previous research and offer feasible advice ...

Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study.

PLoS computational biology
Accurate prediction of epidemics is pivotal for making well-informed decisions for the control of infectious diseases, but addressing heterogeneity in the system poses a challenge. In this study, we propose a novel modelling framework integrating the...

Short-term power load forecasting in China: A Bi-SATCN neural network model based on VMD-SE.

PloS one
This study focuses on improving short-term power load forecasting, a critical aspect of power system planning, control, and operation, especially within the context of China's "dual-carbon" policy. The integration of renewable energy under this polic...

Machine-learning based prediction model for acute kidney injury induced by multiple wasp stings.

Toxicon : official journal of the International Society on Toxinology
Acute kidney injury (AKI) following multiple wasp stings is a severe complication with potentially poor outcomes. Despite extensive research on AKI's risk factors, predictive models for wasp sting-related AKI are limited. This study aims to develop a...

Development and validation of a deep learning-based survival prediction model for pediatric glioma patients: A retrospective study using the SEER database and Chinese data.

Computers in biology and medicine
OBJECTIVE: Develop a time-dependent deep learning model to accurately predict the prognosis of pediatric glioma patients, which can assist clinicians in making precise treatment decisions and reducing patient risk.

Interpretable machine learning for allergic rhinitis prediction among preschool children in Urumqi, China.

Scientific reports
This study aimed to investigate the advantages and applications of machine learning models in predicting the risk of allergic rhinitis (AR) in children aged 2-8, compared to traditional logistic regression. The study analyzed questionnaire data from ...

Integrating dynamic models and neural networks to discover the mechanism of meteorological factors on Aedes population.

PLoS computational biology
Aedes mosquitoes, known as vectors of mosquito-borne diseases, pose significant risks to public health and safety. Modeling the population dynamics of Aedes mosquitoes requires comprehensive approaches due to the complex interplay between biological ...

Relationship matters: Using machine learning methods to predict the mental health severity of Chinese college freshmen during the pandemic period.

Journal of affective disorders
BACKGROUND: Pandemics act as stressors and may lead to frequent mental health disorders. College student, especially freshmen, are particularly susceptible to experiencing intense mental stress reactions during a pandemic. We aimed to identify stable...