Public Health & Policy

Environmental Health

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

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Nordic environmental resilience: balancing air quality and energy efficiency by applying artificial neural network.

Maintaining public health and environmental safety in the Nordic nations calls for a strict plan to ...

Machine Learning Framework for Conotoxin Class and Molecular Target Prediction.

Conotoxins are small and highly potent neurotoxic peptides derived from the venom of marine cone sna...

High spatiotemporal resolution estimation and analysis of global surface CO concentrations using a deep learning model.

Ambient carbon monoxide (CO) is a primary air pollutant that poses significant health risks and cont...

Accuracy is inaccurate: Why a focus on diagnostic accuracy for medical chatbot AIs will not lead to improved health outcomes.

Since its launch in November 2022, ChatGPT has become a global phenomenon, sparking widespread publi...

Significant spatiotemporal changes in atmospheric particulate mercury pollution in China: Insights from meta-analysis and machine-learning.

PM bound mercury (PBM) in the atmosphere is a major component of total mercury, which is a pollutant...

Topic-sentiment analysis of citizen environmental complaints in China: Using a Stacking-BERT model.

Environmental complaints serve as a crucial means for citizens to participate in environmental regul...

Deep learning-assisted detection of psychoactive water pollutants using behavioral profiling of zebrafish embryos.

Water pollution poses a significant risk to the environment and human health, necessitating the deve...

Air quality index prediction with optimisation enabled deep learning model in IoT application.

The development of industrial and urban places caused air pollution, which has resulted in a variety...

Machine learning for air quality index (AQI) forecasting: shallow learning or deep learning?

In this study, several machine learning (ML) models consisting of shallow learning (SL) models (e.g....

Innovations in plastic remediation: Catalytic degradation and machine learning for sustainable solutions.

Plastic pollution is an extreme environmental threat, necessitating novel restoration solutions. The...

Effects of the co-exposure of microplastic/nanoplastic and heavy metal on plants: Using CiteSpace, meta-analysis, and machine learning.

Micro/nanoplastics (MNPs) and heavy metals (HMs) coexist worldwide. Existing studies have reported d...

Derivation of marine water quality criteria for copper based on artificial neural network model.

The water chemical effects of copper have been a focus in the study of water quality criteria (WQC)....

An integrated three-stream network model for discriminating fish feeding intensity using multi-feature analysis and deep learning.

Feed costs constitute a significant part of the expenses in the aquaculture industry. However, feedi...

Imaging pollen using a Raspberry Pi and LED with deep learning.

The production of low-cost, small footprint imaging sensor would be invaluable for airborne global m...

Diagnostic performance of single-lead electrocardiograms for arterial hypertension diagnosis: a machine learning approach.

Awareness and early identification of hypertension is crucial in reducing the burden of cardiovascul...

3DVar sectoral emission inversion based on source apportionment and machine learning.

Air quality models are increasingly important in air pollution forecasting and control. Sectoral emi...

Artificial intelligence application for identifying toxic plant species: A case of poisoning with Datura stramonium.

INTRODUCTION: The management of plant poisonings in the emergency department (ED) presents various c...

Deep learning assists early-detection of hypertension-mediated heart change on ECG signals.

Arterial hypertension is a major risk factor for cardiovascular diseases. While cardiac ultrasound i...

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