AIMC Topic: China

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Optimizing BenMAP health impact assessment with meteorological factor driven machine learning models.

The Science of the total environment
This study aims to address accuracy challenges in assessing air pollution health impacts using Environmental Benefits Mapping and Analysis Program (BenMap), caused by limited meteorological factor data and missing pollutant data. By employing data in...

Unlocking treatment success: predicting atypical antipsychotic continuation in youth with mania.

BMC medical informatics and decision making
PURPOSE: This study aimed to create and validate robust machine-learning-based prediction models for antipsychotic drug (risperidone) continuation in children and teenagers suffering from mania over one year and to discover potential variables for cl...

Green workspace and urban health: exploring the impacts of industrial robotics in pollution emissions and public health.

Frontiers in public health
INTRODUCTION: This study addresses a critical gap in understanding how technological advancements, specifically industrial robots, influence urban pollution emissions and public health. The rapid evolution of technology and changing working condition...

Machine learning-based analysis of heavy metal contamination in Chinese lake basin sediments: Assessing influencing factors and policy implications.

Ecotoxicology and environmental safety
Sediments are important heavy metal sinks in lakes, crucial for ensuring water environment safety. Existing studies mainly focused on well-studied lakes, leaving gaps in understanding pollution patterns in specific basins and influencing factors.We c...

Artificial Intelligence for Early Detection of Pediatric Eye Diseases Using Mobile Photos.

JAMA network open
IMPORTANCE: Identifying pediatric eye diseases at an early stage is a worldwide issue. Traditional screening procedures depend on hospitals and ophthalmologists, which are expensive and time-consuming. Using artificial intelligence (AI) to assess chi...

Soil organic carbon estimation using remote sensing data-driven machine learning.

PeerJ
Soil organic carbon (SOC) is a crucial component of the global carbon cycle, playing a significant role in ecosystem health and carbon balance. In this study, we focused on assessing the surface SOC content in Shandong Province based on land use type...

Joint extraction of Chinese medical entities and relations based on RoBERTa and single-module global pointer.

BMC medical informatics and decision making
BACKGROUND: Most Chinese joint entity and relation extraction tasks in medicine involve numerous nested entities, overlapping relations, and other challenging extraction issues. In response to these problems, some traditional methods decompose the jo...

Pollution loads in the middle-lower Yangtze river by coupling water quality models with machine learning.

Water research
Pollution control and environmental protection of the Yangtze River have received major attention in China. However, modeling the river's pollution load remains challenging due to limited monitoring and unclear spatiotemporal distribution of pollutio...

Semantic-enhanced graph neural network for named entity recognition in ancient Chinese books.

Scientific reports
Named entity recognition (NER) plays a crucial role in the extraction and utilization of knowledge of ancient Chinese books. However, the challenges of ancient Chinese NER not only originate from linguistic features such as the use of single characte...