AIMC Topic: Metals, Heavy
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Effects of the co-exposure of microplastic/nanoplastic and heavy metal on plants: Using CiteSpace, meta-analysis, and machine learning.
Ecotoxicology and environmental safety
Oct 23, 2024
Micro/nanoplastics (MNPs) and heavy metals (HMs) coexist worldwide. Existing studies have reported different or even contradictory toxic effects of co-exposure to MNPs and HMs on plants, which may be related to various influencing factors. In this st...
Machine learning approaches to identify the link between heavy metal exposure and ischemic stroke using the US NHANES data from 2003 to 2018.
Frontiers in public health
Sep 16, 2024
PURPOSE: There is limited understanding of the link between exposure to heavy metals and ischemic stroke (IS). This research aimed to develop efficient and interpretable machine learning (ML) models to associate the relationship between exposure to h...
Progress of machine learning-based biosensors for the monitoring of food safety: A review.
Biosensors & bioelectronics
Sep 12, 2024
Rapid urbanization and growing food demand caused people to be concerned about food safety. Biosensors have gained considerable attention for assessing food safety due to selectivity, and sensitivity but poor stability inherently limits their applica...
Refining hydrogel-based sorbent design for efficient toxic metal removal using machine learning-Bayesian optimization.
Journal of hazardous materials
Aug 30, 2024
Hydrogel-based sorbents show promise in the removal of toxic metals from water. However, optimizing their performance through conventional trial-and-error methods is both costly and challenging due to the inherent high-dimensional parameter space ass...
Tracking the impact of heavy metals on human health and ecological environments in complex coastal aquifers using improved machine learning optimization.
Environmental science and pollution research international
Aug 24, 2024
The rising heavy metal (HM) pollution in coastal aquifers in rapidly urbanizing areas such as Dammam leads to significant risks to public health and environmental sustainability, challenging compliance with Environmental Protection Agency (EPA) guide...
Utilizing machine learning to evaluate heavy metal pollution in the world's largest mangrove forest.
The Science of the total environment
Aug 23, 2024
The world's largest mangrove forest (Sundarbans) is facing an imminent threat from heavy metal pollution, posing grave ecological and human health risks. Developing an accurate predictive model for heavy metal content in this area has been challengin...
Microwave detection technique combined with deep learning algorithm facilitates quantitative analysis of heavy metal Pb residues in edible oils.
Journal of food science
Aug 13, 2024
The heavy metal content in edible oils is intricately associated with their suitability for human consumption. In this study, standard soybean oil was used as a sample to quantify the specified concentration of heavy metals using microwave sensing te...
Assessment of EMR ML Mining Methods for Measuring Association between Metal Mixture and Mortality for Hypertension.
High blood pressure & cardiovascular prevention : the official journal of the Italian Society of Hypertension
Aug 12, 2024
INTRODUCTION: There are limited data available regarding the connection between heavy metal exposure and mortality among hypertension patients.
Contribution assessment and accumulation prediction of heavy metals in wheat grain in a smelting-affected area using machine learning methods.
The Science of the total environment
Aug 11, 2024
Due to the diverse controlling factors and their uneven spatial distribution, especially atmospheric deposition from smelters, assessing and predicting the accumulation of heavy metals (HM) in crops across smelting-affected areas becomes challenging....
Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation.
Journal of hazardous materials
Aug 10, 2024
Urban fragmented vegetable fields offer fresh produce but pose a potential risk of heavy metal (HM) exposure. Thus, this study investigated HM sources and health risks in the soil-vegetable systems of Chongqing's central urban area. Results indicated...
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