AIMC Topic: China

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Predicting art university students' entrepreneurial intention: A hybrid SEM-ANN approach.

PloS one
In recent years, academics and policymakers have increasingly focused on entrepreneurial behavior among university students. While existing studies have explored the entrepreneurial intention (EI) of students from various academic disciplines, few ha...

Entropy-based risk network identification in adolescent self-injurious behavior using machine learning and network analysis.

Translational psychiatry
Adolescent Self-Injurious Behavior (SIB) is a significant global public health issue, with a lifetime prevalence rate of approximately 13.7%. As awareness of SIB rises, there is an urgent need for effective prediction mechanisms to enable early ident...

Interpretable deep learning method to quantify the impact of extreme temperatures on vegetation productivity in China.

Scientific reports
As a key ecological parameter, NPP measures the photosynthetic efficiency of plants in capturing atmospheric carbon. With the warming of the climate, extreme temperature events are frequent, which has exerted a profound influence on NPP. Previous stu...

Deep learning approach for screening neonatal cerebral lesions on ultrasound in China.

Nature communications
Timely and accurate diagnosis of severe neonatal cerebral lesions is critical for preventing long-term neurological damage and addressing life-threatening conditions. Cranial ultrasound is the primary screening tool, but the process is time-consuming...

Factors influencing the adoption of generative artificial intelligence into classroom teaching by university teachers: An empirical study using SPSS PROCESS macros.

PloS one
With the development of science and technology, higher education faces the challenge of AIGC. As one of the central bodies of higher education, it is essential to understand whether teachers accept this new technology and what factors influence their...

Factors that influence technophobia in Chinese older patients with ischemic stroke: a cross-sectional survey.

BMC geriatrics
BACKGROUND: Older patients with ischemic stroke often have a large number of medical needs, technophobia refers to the irrational anxiety and fear of digital technologies such as mobile communication equipment, artificial intelligence and robots, res...

Exploring the influence of hydrological indicators on flow regimes through a data-driven modeling approach in the Huai river basin, China.

Environmental research
Understanding the impact of hydrological indicators on flow regimes is essential for sustainable water resource management. This study presents a data-driven framework integrating eXtreme Gradient Boosting (XGBoost) with SHapley Additive exPlanations...

Exploring GPT-4o's multimodal reasoning capabilities with panoramic radiograph: the role of prompt engineering.

Clinical oral investigations
OBJECTIVES: The aim of this study was to evaluate GPT-4o's multimodal reasoning ability to review panoramic radiograph (PR) and verify its radiologic findings, while exploring the role of prompt engineering in enhancing its performance.

Applications of artificial intelligence and urban innovation performance: A quasi-natural experiment based on the pilot zones for the innovative application of artificial intelligence.

PloS one
Innovation is the core driving force behind the ability to cope with risks and enhance urban competitiveness. Against the backdrop of frequent global crises and intensified competition, improving urban innovation performance is important. This study ...

A Deep Learning Framework for Using Search Engine Data to Predict Influenza-Like Illness and Distinguish Epidemic and Nonepidemic Seasons: Multifeature Time Series Analysis.

Journal of medical Internet research
BACKGROUND: The seasonal influenza epidemic poses a persistent and severe threat to global public health. Web-based search data are recognized as a valuable source for forecasting influenza or other respiratory tract infection epidemics. Current infl...