AIMC Topic: Cadmium
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Systemic inflammation mediates the relationship between urinary cadmium and chronic cough risk: findings based on multiple statistical models.
Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine
May 7, 2025
Epidemiological research examining the relationship between urinary cadmium and the risk of chronic cough remains scarce. This study included 2965 participants for a cross-sectional study from the NHANES. The weighted quantile sum (WQS) regression, b...
Stricter cadmium and lead standards needed for organic fertilizers in China.
The Science of the total environment
Apr 30, 2025
This study aims to evaluate the adequacy of China's national standards for heavy metals in organic fertilizers by predicting their concentrations in grains using machine leaning. A comprehensive dataset was collected from literature, including soil p...
Estimating soil cadmium concentration using multi-source UAV imagery and machine learning techniques.
Environmental monitoring and assessment
Apr 24, 2025
Urbanization and industrialization have led to widespread soil heavy metals contamination, posing significant risks to ecosystems and human health. Conventional methods for mapping heavy metal distribution, which rely on soil sampling followed by che...
Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.
Frontiers in public health
Apr 16, 2025
BACKGROUND: Exposure to heavy metals has been implicated in adverse auditory health outcomes, yet the precise relationships between heavy metal biomarkers and hearing status remain underexplored. This study leverages a machine learning framework to i...
Nondestructive detection of cadmium content in oilseed rape leaves under different silicon environments using deep transfer learning and Vis-NIR hyperspectral imaging.
Food chemistry
Mar 8, 2025
In this paper, a transfer stack denoising autoencoder (T-SDAE) algorithm is proposed to implement the migration of cadmium (Cd) prediction depth characteristic model of oilseed rape leaves in different silicon environments. Stacked denoising autoenco...
CZT-based photon-counting-detector CT with deep-learning reconstruction: image quality and diagnostic confidence for lung tumor assessment.
Japanese journal of radiology
Mar 7, 2025
PURPOSE: This is a preliminary analysis of one of the secondary endpoints in the prospective study cohort. The aim of this study is to assess the image quality and diagnostic confidence for lung cancer of CT images generated by using cadmium-zinc-tel...
A novel graph convolutional neural network model for predicting soil Cd and As pollution: Identification of influencing factors and interpretability.
Ecotoxicology and environmental safety
Feb 19, 2025
Soil pollution caused by toxic metals poses serious threats to the ecological environment and human well-being. Accurately predicting toxic metal concentrations is critical for safeguarding soil environmental security. However, the distribution of so...
Blood metal levels predict digestive tract cancer risk using machine learning in a U.S. cohort.
Scientific reports
Jan 8, 2025
BACKGROUND: Environmental metal exposure has been implicated in the development of digestive tract cancers, although the specific associations remain poorly defined. This study aimed to investigate the relationship between blood metal levels and the ...
Quantifying the contributions of factors to bioaccessible Cd and Pb in soil using machine learning.
Journal of hazardous materials
Jan 2, 2025
The bioaccessibility of cadmium (Cd) and lead (Pb) in the gastrointestinal tract is crucial for health risk assessments of contaminated soils. However, variability in In vitro analytical conditions and soil properties introduces bias and uncertainty ...
Enhancing the estimation of cadmium content in rice leaves by integrating vegetation indices and color indices using machine learning.
Ecotoxicology and environmental safety
Dec 16, 2024
Cadmium (Cd) is a heavy metal recognized for its notable biotoxicity. Excessive Cd levels can have detrimental effects on crop growth, development, and yield. Real-time, rapid, and nondestructive monitoring of Cd content in leaves (LCd) is essential ...
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