Public Health & Policy

Environmental Health

Latest AI and machine learning research in environmental health for healthcare professionals.

6,302 articles
Stay Ahead - Weekly Environmental Health research updates
Subscribe
Browse Specialties
Showing 169-189 of 6,302 articles
Machine Learning-Enhanced Prediction for Soil-to-Air VOC Emission and Environmental Impact Pertaining Contaminated Fractured Aquifers.

How to scientifically and efficiently quantify the impact and hazards of volatile organic compounds ...

Advancing Enzyme-Based Detoxification Prediction with ToxZyme: An Ensemble Machine Learning Approach.

The aaccurate prediction of enzymes with environment detoxification functions is crucial, not only t...

Predicting the amount of toxic metals and metalloids in silt loading using neural networks.

Material deposited on road surfaces, called road dust, are known to contain different toxic elements...

Interpretable machine learning reveals the importance of geography and landscape arrangement for surface water quality across China.

Elucidating the influence of land use patterns on surface water quality is crucial for effective wat...

The environmental risk of heterogeneous oxidation is unneglectable: Time-resolved assessments beyond typical intermediate investigation.

The safety of advanced oxidation processes is paramount, surpassing treatment efficiency concerns. H...

Are we underestimating the driving factors and potential risks of freshwater microplastics from in situ and in silico perspective?

The high loads of heterogeneous microplastics (MPs) in water system sparked the exploration of MPs s...

Unveiling drug-induced osteotoxicity: A machine learning approach and webserver.

Drug-induced osteotoxicity refers to the harmful effects certain pharmaceuticals have on the skeleta...

The interpretable machine learning model for depression associated with heavy metals via EMR mining method.

Limited research exists on the association between depression and heavy metal exposure. This study a...

Unraveling the complexity of organophosphorus pesticides: Ecological risks, biochemical pathways and the promise of machine learning.

Organophosphorus pesticides (OPPs) are widely used in agriculture but pose significant ecological an...

Neural Network With Attention Mechanism for Abnormality Detection and Localization in Diffusive Molecular Communication.

Diffusive molecular communication (DMC) is an emerging paradigm in nanotechnology, which provides bi...

Resolving multi-image spatial lipidomic responses to inhaled toxicants by machine learning.

Regional responses to inhaled toxicants are essential to understand the pathogenesis of lung disease...

Assessing potential toxic metal threats in tea growing soils of India with soil health indices and machine learning technologies.

This study explores the impact of potentially toxic metals (PTMs) contamination in Indian tea-growin...

Reimagining the Kendall plot: using N and O of nitrate and advanced machine learning to improve N pollutant source classification.

Nitrate () pollution is a serious water quality issue in many countries due to contamination of lake...

Machine learning for predictive mapping of exceedance probabilities for potentially toxic elements in Czech farmland.

For efficient decision-making and optimal land management trajectories, information on soil properti...

Deep Learning-Based Detection of Aflatoxin B1 Contamination in Almonds Using Hyperspectral Imaging: A Focus on Optimized 3D Inception-ResNet Model.

Aflatoxin B1, a toxic carcinogen frequently contaminating almonds, nuts, and food products, poses si...

Forecasting the concentration of the components of the particulate matter in Poland using neural networks.

Air pollution is a significant global challenge with profound impacts on human health and the enviro...

Smart waste management and air pollution forecasting: Harnessing Internet of things and fully Elman neural network.

As the Internet of things (IoT) continues to transform modern technologies, innovative applications ...

Accurate prediction of spatial distribution of soil heavy metal in complex mining terrain using an improved machine learning method.

Accurate prediction of heavy metals (HMs) spatial distribution in mining areas is crucial for pollut...

Browse Specialties