AI Medical Compendium Journal:
Ecotoxicology and environmental safety

Showing 21 to 30 of 52 articles

Improving the construction and prediction strategy of the Air Quality Health Index (AQHI) using machine learning: A case study in Guangzhou, China.

Ecotoxicology and environmental safety Nov 9, 2024
Effectively capturing the risk of air pollution and informing residents is vital to public health. The widely used Air Quality Index (AQI) has been criticized for failing to accurately represent the non-threshold linear relationship between air pollu...
Air Pollution Particulate Matter China Environmental Monitoring Air Pollutants Humans Machine Learning
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Mining soil heavy metal inversion based on Levy Flight Cauchy Gaussian perturbation sparrow search algorithm support vector regression (LSSA-SVR).

Ecotoxicology and environmental safety Nov 8, 2024
Soil heavy metal pollution in mining areas poses severe challenges to the ecological environment. In recent years, machine learning has been widely used in heavy metal inversion by hyperspectral data. However, deterministic algorithms and probabilist...
Soil Environmental Monitoring Support Vector Machine Mining Normal Distribution Soil Pollutants Metals, Heavy Algorithms
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Big data from population surveys and environmental monitoring-based machine learning predictions of indoor PM in 22 cities in China.

Ecotoxicology and environmental safety Nov 5, 2024
Many studies have confirmed that PM exposure can cause a variety of diseases. Because people spend most of their time indoors, exposure to PM in indoor environments is critical to population health. Large-population, long-term, continuous, and accura...
Big Data Cities Environmental Monitoring Humans Machine Learning China Air Pollutants Air Pollution, Indoor Particulate Matter
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Trends in the prevalence of osteoporosis and effects of heavy metal exposure using interpretable machine learning.

Ecotoxicology and environmental safety Oct 28, 2024
There is limited evidence that heavy metals exposure contributes to osteoporosis. Multi-parameter scoring machine learning (ML) techniques were developed using National Health and Nutrition Examination Survey data to predict osteoporosis based on hea...
Machine Learning Osteoporosis Humans Nutrition Surveys Male Female Cadmium Environmental Pollutants Middle Aged Aged Metals, Heavy Environmental Exposure Prevalence Adult China
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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 Nanoparticles Soil Pollutants Plants Microplastics Cadmium Metals, Heavy
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Identifying cardiovascular disease risk in the U.S. population using environmental volatile organic compounds exposure: A machine learning predictive model based on the SHAP methodology.

Ecotoxicology and environmental safety Oct 23, 2024
BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of mortality globally. Environmental pollutants, specifically volatile organic compounds (VOCs), have been identified as significant risk factors. This study aims to develop a machine l...
Air Pollutants Environmental Pollutants Environmental Exposure Volatile Organic Compounds Risk Assessment Nutrition Surveys United States Risk Factors Aged Young Adult Cardiovascular Diseases Adult Humans Middle Aged Machine Learning Male Female
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Identification of endocrine-disrupting chemicals targeting key OP-associated genes via bioinformatics and machine learning.

Ecotoxicology and environmental safety Oct 9, 2024
Osteoporosis (OP), a metabolic disorder predominantly impacting postmenopausal women, has seen considerable progress in diagnosis and treatment over the past few decades. However, the intricate interplay between genetic factors and endocrine disrupto...
Molecular Docking Simulation Computational Biology Environmental Pollutants Endocrine Disruptors Humans Machine Learning Female
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Prediction and validation of mild cognitive impairment in occupational dust exposure population based on machine learning.

Ecotoxicology and environmental safety Sep 26, 2024
OBJECTIVE: Workers exposed to dust for extended periods may experience varying degrees of cognitive impairment. However, limited research exists on the associated risk factors. This study aims to identify key variables using machine learning algorith...
Cognitive Dysfunction Occupational Exposure Logistic Models Dust Male Middle Aged China Female Risk Factors Humans Adult Machine Learning
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Application of machine learning approaches to predict ammonium nitrogen transport in different soil types and evaluate the contribution of control factors.

Ecotoxicology and environmental safety Aug 17, 2024
The loss of nitrogen in soil damages the environment. Clarifying the mechanism of ammonium nitrogen (NH-N) transport in soil and increasing the fixation of NH-N after N application are effective methods for improving N use efficiency. However, the ma...
Soil Pollutants Machine Learning Nitrogen Soil Ammonium Compounds Environmental Monitoring
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Use of machine learning algorithms to determine the relationship between air pollution and cognitive impairment in Taiwan.

Ecotoxicology and environmental safety Aug 15, 2024
Air pollution has become a major global threat to human health. Urbanization and industrialization over the past few decades have increased the air pollution. Plausible connections have been made between air pollutants and dementia. This study used m...
Taiwan Air Pollutants Air Pollution Cognitive Dysfunction Nitric Oxide Environmental Monitoring Carbon Monoxide Humans Ozone Nitrogen Dioxide Machine Learning Particulate Matter Algorithms Environmental Exposure Male Female Middle Aged Aged
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