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Environmental Exposure

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Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.

Frontiers in public health
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...

Machine learning model for age related macular degeneration based on pesticides: the National Health and Nutrition Examination Survey 2007-2008.

Frontiers in public health
Age-related macular degeneration (AMD) is the most common cause of irreversible deterioration of vision in older adults. Previous studies have found that exposure to pesticides can lead to a worsening of AMD. In this paper, information on pesticide e...

Advancing exposure science through artificial intelligence: Neural ordinary differential equations for predicting blood concentrations of volatile organic compounds.

Ecotoxicology and environmental safety
Volatile organic compounds (VOCs) are a significant concern for human health and environmental safety, requiring accurate models to predict their concentrations in body fluids for effective risk assessments. This study evaluates the application of ne...

Influence pathways of noise exposure on people's negative emotions and health across different activity contexts: A neural network-based double machine learning approach.

Health & place
Noise is a major global environmental issue that raises concerns about both mental and physical health. However, few studies have investigated the mediating role of emotions in the pathways linking noise exposure to health outcomes. Additionally, man...

Artificial intelligence: A key fulcrum for addressing complex environmental health issues.

Environment international
Environmental health (EH) is a complex and interdisciplinary field dedicated to the examination of environmental behaviours, toxicological effects, health risks, and strategies for mitigating harmful environmental factors. Traditional EH research inv...

Spatial analysis of air pollutant exposure and its association with metabolic diseases using machine learning.

BMC public health
BACKGROUND: Metabolic diseases (MDs), exemplified by diabetes, hypertension, and dyslipidemia, have become increasingly prevalent with rising living standards, posing significant public health challenges. The MDs are influenced by a complex interplay...

An informed machine learning based environmental risk score for hypertension in European adults.

Artificial intelligence in medicine
BACKGROUND: The exposome framework seeks to unravel the cumulated effects of environmental exposures on health. However, existing methods struggle with challenges including multicollinearity, non-linearity and confounding. To address these limitation...

Refining source-specific lung cancer risk assessment from PM-bound PAHs: Integrating component-based potency factors and machine learning in Ningbo, China.

Ecotoxicology and environmental safety
The component-based potency factor approach, combined with benzo[a]pyrene (BaP) unit risk values from the World Health Organization (WHO), is commonly used to assess lung excess cancer risk (LECR) from polycyclic aromatic hydrocarbons (PAHs). However...

Exploring pesticide risk in autism via integrative machine learning and network toxicology.

Ecotoxicology and environmental safety
Autism Spectrum Disorder (ASD) is a prevalent neurodevelopmental condition influenced by both genetic and environmental factors, including pesticide exposure. This study aims to investigate the pathogenic mechanisms of ASD and identify potential caus...

Machine Learning Models for Predicting Pediatric Hospitalizations Due to Air Pollution and Humidity: A Retrospective Study.

Pediatric pulmonology
BACKGROUND: Exposure to air pollution and meteorological conditions, such as humidity, has been linked to adverse respiratory health outcomes in children. This study aims to develop predictive models for pediatric hospitalizations based on both envir...