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 211-231 of 6,302 articles
Enhanced water quality prediction model using advanced hybridized resampling alternating tree-based and deep learning algorithms.

Water quality modeling in riverine systems is crucial for effective water resource management and po...

Deep structured learning with vision intelligence for oral carcinoma lesion segmentation and classification using medical imaging.

Oral carcinoma (OC) is a toxic illness among the most general malignant cancers globally, and it has...

Machine learning-based analysis of microplastic-induced changes in anaerobic digestion parameters influencing methane yield.

Microplastics (MPs) present significant challenges for anaerobic digestion (AD) processes used in en...

Dissolved organic carbon estimation in lakes: Improving machine learning with data augmentation on fusion of multi-sensor remote sensing observations.

This paper presents a novel approach for estimating Dissolved Organic Carbon (DOC) concentrations in...

Uncovering soil heavy metal pollution hotspots and influencing mechanisms through machine learning and spatial analysis.

Soil heavy metal (HM) pollution is a significant and widespread environmental issue in China, highli...

Utilizing 12-lead electrocardiogram and machine learning to retrospectively estimate and prospectively predict atrial fibrillation and stroke risk.

BACKGROUND: The stroke risk in patients with subclinical atrial fibrillation (AF) is underestimated....

High-resolution spatio-temporal estimation of street-level air pollution using mobile monitoring and machine learning.

High spatio-temporal resolution street-level air pollution (SLAP) estimation is essential for urban ...

Generalizable deep neural networks for image quality classification of cervical images.

Successful translation of artificial intelligence (AI) models into clinical practice, across clinica...

Learning from leading indicators to predict long-term dynamics of hourly electricity generation from multiple resources.

Electricity is generated through various resources and then flows between regions via a complex syst...

A novel graph convolutional neural network model for predicting soil Cd and As pollution: Identification of influencing factors and interpretability.

Soil pollution caused by toxic metals poses serious threats to the ecological environment and human ...

Environment sustainability with smart grid sensor.

Environmental sustainability is a pressing global concern, with energy conservation and efficient ut...

Machine learning insights into calcium phosphate nucleation and aggregation.

In this study, we utilized machine learning interatomic potentials (MLIPs) to investigate the nuclea...

A study on the impact of meteorological and emission factors on PM concentrations based on machine learning.

PM pollution, a major environmental and health concern, is influenced by a complex interplay of emis...

Managerial myopia and its barrier to green innovation in high-pollution enterprises: A machine learning approach.

Green technology innovation has become a vital remedy in response to the world's growing ecological ...

Exploring the response of bacterial community functions to microplastic features in lake ecosystems through interpretable machine learning.

Microplastics (MPs) are ubiquitous and have various characteristics. However, their impacts on bacte...

A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors.

Accurate air pollution monitoring is critical to understand and mitigate the impacts of air pollutio...

Explainable AI-driven scalogram analysis and optimized transfer learning for sleep apnea detection with single-lead electrocardiograms.

Sleep apnea, a fatal sleep disorder causing repetitive respiratory cessation, requires immediate int...

Integration of machine learning and meta-analysis reveals the behaviors and mechanisms of antibiotic adsorption on microplastics.

Microplastics (MPs) can adsorb antibiotics (ATs) to cause combined pollution in the environment. Res...

Chemical Space Networks Enhance Toxicity Recognition via Graph Embedding.

Chemical space networks (CSNs) are a new effective strategy for detecting latent chemical patterns i...

Combining deep learning and machine learning techniques to track air pollution in relation to vegetation cover utilizing remotely sensed data.

The rapid urban expansion in Dhaka, the capital of Bangladesh, has escalated air pollution levels an...

Browse Specialties