Environmental Health

Novel concept for the healthy population influencing factors.

In the rapid urbanization process in China, due to reasons such as employment, education, and family reunification, the number of mobile population without registered residence in the local area has increased significantly. By 2020, the group had a population of 276 million, accounting for over 20% of the total population, making significant contributions to urban economic development and resource...

Natural factor-based spatial prediction and source apportionment of typical heavy metals in Chinese surface soil: Application of machine learning models.

Predicting the natural distribution of heavy metals (HMs) in soil is important to understand the potential risk of pollution. However, suitable technologies are still lacking for wide scale due to the large spatial heterogeneity. In this study, we developed machine learning models for predicting natural contents of five typical HMs in soil, including As, Cd, Cr, Hg and Pb. It was found that the op...

Selectively Quantify Toxic Pollutants in Water by Machine Learning Empowered Electrochemical Biosensors.

Electroactive biofilm (EAB) sensors have become pivotal in water quality detection and early ecological risk warnings due to their remarkable sensitiv...

The Effect of Different Bleaching Techniques Using 6% Hydrogen Peroxide: Penetration Inside the Pulp Cavity, Bleaching Efficacy and Toxicity.

This in vitro study aimed to quantify the penetration of hydrogen peroxide (HP), bleaching efficacy (BE) and toxicity in larvae in different bleaching...

ESR Essentials: how to get to valuable radiology AI: the role of early health technology assessment-practice recommendations by the European Society of Medical Imaging Informatics.

AI tools in radiology are revolutionising the diagnosis, evaluation, and management of patients. However, there is a major gap between the large numbe...

Novel method for predicting concentrations of incineration flue gas based on waste composition and machine learning.

The complex composition of solid waste leads to the variability of flue gas emissions during its incineration, which poses a challenge to the stable o...

Evaluating drivers of PM air pollution at urban scales using interpretable machine learning.

Reducing urban fine particulate matter (PM) concentrations is essential for China to achieve the Sustainable Development Goals (SDGs). Identifying the...

Graphene FET biochip on PCB reinforced by machine learning for ultrasensitive parallel detection of multiple antibiotics in water.

Antibiotics like Ciprofloxacin (Cfx), tetracycline (Tet) and Tobramycin (Tob) are commonly used against a broad-spectrum of bacterial infection. Recen...

The development of classification-based machine-learning models for the toxicity assessment of chemicals associated with plastic packaging.

Assessing chemical toxicity in materials like plastic packaging is critical to safeguarding public health. This study presents the development of clas...

Fuzzy set-based decision support system for hydrogen sulfide removal technology selection in natural gas processing: a sustainability and efficiency perspective.

Removing hydrogen sulfide (HS) toxic and corrosive gas from the natural gas processing and utilization industry is a challenging problem for managers ...

Does industrial robot adoption inhibit environmental pollution in China? An empirical study on energy consumption and green technology innovation.

In this research, we develop a theoretical model to examine the relationship between the adoption of industrial robots and environmental pollution. Ad...

SERS-AI Based Detection and Bioanalysis of Malodorous Components in Kitchen Waste.

The prevention and control of odor gas generated from kitchen waste are significant missions in research on environmental pollution. Because of the hi...

Artificial intelligence-driven assessment of critical inputs for lead adsorption by agro-food wastes in wastewater treatment.

Due to environmental concerns and economic value, the adsorption process using agricultural wastes is one of the promising methods to remove lead (Pb)...

A Multicenter Evaluation of the Impact of Therapies on Deep Learning-Based Electrocardiographic Hypertrophic Cardiomyopathy Markers.

Artificial intelligence-enhanced electrocardiography (AI-ECG) can identify hypertrophic cardiomyopathy (HCM) on 12-lead ECGs and offers a novel way to...

Spatiotemporal variations of PM and ozone in urban agglomerations of China and meteorological drivers for ozone using explainable machine learning.

Ozone pollution was widely reported along with PM reduction since 2013 in China. However, the meteorological drivers for ozone varying with different ...

Improving PM and PM predictions in China from WRF_Chem through a deep learning method: Multiscale depth-separable UNet.

Accurate predictions of atmospheric particulate matter can be applied in providing services for air pollution prevention and control. However, the for...

Deployment of intelligent irrigation monitoring system with Android app for machine learning prediction.

Water is a fundamental necessity for humans and a critical resource in agriculture. However, water scarcity poses a significant challenge, especially ...

A Physically Constrained Deep-Learning Fusion Method for Estimating Surface NO Concentration from Satellite and Ground Monitors.

Accurate estimation of atmospheric chemical concentrations from multiple observations is crucial for assessing the health effects of air pollution. Ho...

Machine learning estimates on the impacts of detection times on wildfire suppression costs.

As climate warming exacerbates wildfire risks, prompt wildfire detection is an essential step in designing an efficient suppression strategy, monitori...

Uncovering global risk to human and ecosystem health from pesticides in agricultural surface water using a machine learning approach.

Pesticides typically co-occur in agricultural surface waters and pose a potential threat to human and ecosystem health. As pesticide screening in glob...