Public Health & Policy

Environmental Health

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

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Modeling health outcomes of air pollution in the Middle East by using support vector machines and neural networks.

This study investigates the impact of air pollution on health outcomes in Middle Eastern countries, ...

Ensemble machine learning framework for predicting maternal health risk during pregnancy.

Maternal health risks can cause a range of complications for women during pregnancy. High blood pres...

Performance analysis of machine learning models for AQI prediction in Gorakhpur City: a critical study.

Air pollution and climate change are two complementary forces that directly or indirectly affect the...

Detecting floating litter in freshwater bodies with semi-supervised deep learning.

Researchers and practitioners have extensively utilized supervised Deep Learning methods to quantify...

3DECG-Net: ECG fusion network for multi-label cardiac arrhythmia detection.

Cardiovascular diseases represent the leading global cause of death, typically diagnosed and address...

Assessment of noise pollution-prone areas using an explainable geospatial artificial intelligence approach.

This research aims to use the power of geospatial artificial intelligence (GeoAI), employing the cat...

The Role of Complicated Grief in Health Inequities in American Indian Communities.

Complicated grief is both a cause and a consequence of health inequities in Native (American Indian/...

Efficient plastic detection in coastal areas with selected spectral bands.

Marine plastic pollution poses significant ecological, economic, and social challenges, necessitatin...

Application and innovation of artificial intelligence models in wastewater treatment.

At present, as the problem of water shortage and pollution is growing serious, it is particularly im...

A coordinated adaptive multiscale enhanced spatio-temporal fusion network for multi-lead electrocardiogram arrhythmia detection.

The multi-lead electrocardiogram (ECG) is widely utilized in clinical diagnosis and monitoring of ca...

Combining Google traffic map with deep learning model to predict street-level traffic-related air pollutants in a complex urban environment.

BACKGROUND: Traffic-related air pollution (TRAP) is a major contributor to urban pollution and varie...

Machine learning-driven prediction of phosphorus adsorption capacity of biochar: Insights for adsorbent design and process optimization.

Phosphorus (P) pollution in aquatic environments poses significant environmental challenges, necessi...

Conv-RGNN: An efficient Convolutional Residual Graph Neural Network for ECG classification.

BACKGROUND AND OBJECTIVE: Electrocardiogram (ECG) analysis is crucial in diagnosing cardiovascular d...

Knowledge-based machine learning for predicting and understanding the androgen receptor (AR)-mediated reproductive toxicity in zebrafish.

Traditional methods for identifying endocrine-disrupting chemicals (EDCs) that activate androgen rec...

Refining hydrogel-based sorbent design for efficient toxic metal removal using machine learning-Bayesian optimization.

Hydrogel-based sorbents show promise in the removal of toxic metals from water. However, optimizing ...

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