Environmental Health

A Horizon Scan to Support Chemical Pollution-Related Policymaking for Sustainable and Climate-Resilient Economies.

While chemicals are vital to modern society through materials, agriculture, textiles, new technology...

Deep learning for asbestos counting.

The PCM (phase contrast microscopy) method for asbestos counting needs special sample treatments, he...

Multiclass classification of environmental chemical stimuli from unbalanced plant electrophysiological data.

Plant electrophysiological response contains useful signature of its environment and health which ca...

Prediction of atmospheric pollutants in urban environment based on coupled deep learning model and sensitivity analysis.

Accurate and efficient predictions of pollutants in the atmosphere provide a reliable basis for the ...

Synthesis of δ-MnO via ozonation routine for low temperature formaldehyde removal.

Nowadays, it is still a challenge to prepared high efficiency and low cost formaldehyde (HCHO) remov...

Water quality assessment of deep learning-improved comprehensive pollution index: a case study of Dagu River, Jiaozhou Bay, China.

In the past few decades, with the country's rapid development, water pollution has become a signific...

Application of artificial intelligence in solar and wind energy resources: a strategy to deal with environmental pollution.

Environmental pollution has become a significant concern of nations. International organizations, lo...

Graph-based machine learning improves just-in-time defect prediction.

The increasing complexity of today's software requires the contribution of thousands of developers. ...

Using artificial intelligence to enhance the diagnostic accuracy of the 12-lead electrocardiogram in patients with suspected acute pulmonary embolism - Can you teach an old dog new tricks?

Artificial intelligence-based diagnosis of acute pulmonary embolism: Development of a machine learning model using 12-lead electrocardiogram.

INTRODUCTION: Pulmonary embolism (PE) is a life-threatening condition, in which diagnostic uncertain...

Enhanced rainfall prediction performance via hybrid empirical-singular-wavelet-fuzzy approaches.

Rainfall is a vital process in the hydrological cycle of the globe. Accessing reliable and accurate ...

Will biomimetic robots be able to change a hivemind to guide honeybees' ecosystem services?

We study whether or not a group of biomimetic waggle dancing robots is able to significantly influen...

Application of synthetic data in the training of artificial intelligence for automated quality assurance in magnetic resonance imaging.

BACKGROUND: Magnetic resonance imaging scanner faults can be missed during routine quality assurance...

Coupling ANFIS with ant colony optimization (ACO) algorithm for 1-, 2-, and 3-days ahead forecasting of daily streamflow, a case study in Poland.

Finding an efficient and reliable streamflow forecasting model has always been an important challeng...

Deep Learning-Based Road Traffic Noise Annoyance Assessment.

With the development of urban road traffic, road noise pollution is becoming a public concern. Contr...

The predictive model for COVID-19 pandemic plastic pollution by using deep learning method.

Pandemic plastics (e.g., masks, gloves, aprons, and sanitizer bottles) are global consequences of CO...

Artificial intelligence and machine learning disciplines with the potential to improve the nanotoxicology and nanomedicine fields: a comprehensive review.

The use of nanomaterials in medicine depends largely on nanotoxicological evaluation in order to ens...

Stimulus classification with electrical potential and impedance of living plants: comparing discriminant analysis and deep-learning methods.

The physiology of living organisms, such as living plants, is complex and particularly difficult to ...

Deep learning augmented ECG analysis to identify biomarker-defined myocardial injury.

Chest pain is a common clinical complaint for which myocardial injury is the primary concern and is ...

PM2.5 Concentration Prediction Model: A CNN-RF Ensemble Framework.

Although many machine learning methods have been widely used to predict PM2.5 concentrations, these ...

The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond.

BACKGROUND: Evaluating the impact of environmental exposures on organism health is a key goal of mod...