Environmental Health

Evaluating deep learning time series models for PM2.5 forecasting across diverse horizons.

Air pollution, particularly PM2.5, poses a major health challenge in urban areas such as Chengdu, China, where basin topography and intense emission sources exacerbate pollutant concentrations. This study evaluates four deep-learning time series algorithms-LSTM, CNN-LSTM, Transformer, and Transformer-LSTM-for PM2.5 forecasting, comparing univariate and four multivariate configurations incorporatin...

Machine learning reveals ecological thresholds and predicts future bacterial community shifts in a chronically eutrophic estuary.

Effectively managing eutrophic estuaries under climate change requires a quantitative understanding of how microbial communities respond to multiple environmental stressors. However, predicting these responses is challenging due to complex, non-linear interactions. This study addresses this gap by developing a machine learning framework to model the seasonal dynamics of the bacterial community in ...

A Smartphone-Read, Machine Learning-Enhanced Lanthanide Hydrogel Sensor for Multimodal and On-Site Detection of Kanamycin in Food Safety.

Residual kanamycin from veterinary use poses a persistent threat to environmental safety and public health, as its accumulation in water systems and a...

A novel graph convolutional neural network on K neighbors model for fine-grained air pollution distribution mapping based on sparse monitoring.

This article aims to predict the concentration of air pollutants at any unmonitored location based on sparse monitoring points in the monitoring area,...

Assessing greenspace and cardiovascular disease risk through deep learning analysis of street-view imagery in the US-based nationwide Nurses' Health Study.

BACKGROUND: Living near greenspace is associated with decreased cardiovascular disease (CVD). Greenspace estimates, however, typically represent all t...

Combined effects of persistent organic pollutants and endocrine-disrupting chemicals on thyroid disease risk: A WQS-XGBoost analysis of US population data.

To assess the combined effects of mixed persistent organic pollutants and endocrine-disrupting chemicals on thyroid disease risk, we analyzed data fro...

[Evaluation of an interpretable 12-lead ECG automatic diagnosis model based on deep feature fusion].

OBJECTIVES: To enhance the accuracy and reliability of 12-lead electrocardiogram (ECG) automatic diagnosis. METHODS: Herein we propose a 12-lead ECG a...

uPVC-Net: A Universal Premature Ventricular Contraction Detection Deep Learning Algorithm.

INTRODUCTION: Premature Ventricular Contractions (PVCs) are common cardiac arrhythmias originating from the ventricles. Accurate detection remains cha...

Ambient Air Pollution, Greenness and Frailty in an Elder Asian Population: A Multi-Center Study with Long-Term Exposure.

BACKGROUND: Long-term exposure to air pollution has been linked to adverse health outcomes in older adults; however, its association with frailty, par...

A Framework Integrating Single-Cell Metallomic Data in Health Effect Analysis via Quantile Features and Machine Learning.

Heavy and essential metals coexist in a cell, collectively participate in cellular biological processes, and lead to overall health consequences. Howe...

Surface water quality prediction via an MLA-Mamba hybrid neural network with GRPO optimization.

Surface water quality forecasting is crucial for pollution early warning and sustainable water resource management. However, accurate prediction of ke...

Indoor air quality in primary schools: real-time monitoring and predictive modeling of PM10 in Kenitra, Morocco.

The health of children may be adversely influenced by the air quality in schools because they are more sensitive to indoor air pollutants. PM10, which...

Data-driven assessment of nitrogen and phosphorus buffering capacity across 460 Chinese watersheds: Spatial patterns, drivers, and future projections.

Watershed nitrogen and phosphorus buffering capacity refers to the capacity of a watershed to retain nitrogen and phosphorus in soil, groundwater, and...

Fluorescence from dual molecular rotors allows sensitive detection of widespread brain pathology in a mouse model of Alzheimer's disease.

Amyloid fibrils formed by the misfolding and aggregation of proteins are a pathological hallmark of many neurodegenerative conditions including Alzhei...

The effect of air pollution and household environmental indicators on anemia status among under-five children in low-middle income countries: exploring potential machine learning applications on demographic and health surveys.

Exposure to air pollution has been associated with anemia in children, but little effort has been made in low- and middle-income countries (LMICs) in ...

Restraint Quality, Not Quantity, Predicts Peptide-Protein Docking Outcomes.

Understanding protein-peptide interactions is essential for uncovering cellular signaling mechanisms and advancing therapeutic development, as these i...

A review of remote sensing technology for plastic waste monitoring.

Plastic waste pollution has become a critical environmental challenge that requires innovative monitoring approaches to support effective environmenta...

Wearable device derived electrocardiographic age and its association with atrial fibrillation.

Artificial intelligence (AI)-derived electrocardiographic (ECG) age is a promising marker of atrial fibrillation (AF) risk. We developed PROPHECG-Age ...

Pollution risk exposure assessment for Portugal and the Baltic Sea with an emphasis on shadow fleets.

Recent geopolitical developments influence trade flows and risk exposure of shipping. This comprehensive study based on 45.2 million estimates of the ...

A comprehensive soil pollution monitoring system based on convolutional recursive sequence network and terahertz spectroscopy.

BACKGROUND: Accurate analysis of the total amount of heavy metals and their distribution patterns in soil can aid in determining the extent of soil po...