AI Medical Compendium Journal:
Chemosphere

Showing 111 to 120 of 147 articles

Deep learning for predicting the occurrence of cardiopulmonary diseases in Nanjing, China.

Chemosphere
The efficiency of disease prevention and medical care service necessitated the prediction of incidence. However, predictive accuracy and power were largely impeded in a complex system including multiple environmental stressors and health outcome of w...

The use of artificial neural network (ANN) for modeling adsorption of sunset yellow onto neodymium modified ordered mesoporous carbon.

Chemosphere
Discharging coloring products in water bodies has degraded water quality irreversibly over the past several decades. Order mesoporous carbon (OMC) was modified by embedding neodymium(III) chloride on the surface of OMC to enhance the adsorptive remov...

Supervised machine learning for source allocation of per- and polyfluoroalkyl substances (PFAS) in environmental samples.

Chemosphere
Environmental contamination by per- and polyfluoroalkyl substances (PFAS) is widespread, because of both their decades of use, and their persistence in the environment. These factors can make identification of the source of contamination in samples a...

Modeling and optimization of imidacloprid degradation by catalytic percarbonate oxidation using artificial neural network and Box-Behnken experimental design.

Chemosphere
Due to its toxicity and persistence, pesticide pollution poses a serious threat to human health and the environment. Imidacloprid or IMD is an archetypal neonicotinoid insecticide commonly used to protect a variety of crops worldwide. The present stu...

Hybrid decision tree-based machine learning models for short-term water quality prediction.

Chemosphere
Water resources are the foundation of people's life and economic development, and are closely related to health and the environment. Accurate prediction of water quality is the key to improving water management and pollution control. In this paper, t...

Radial basis function artificial neural network able to accurately predict disinfection by-product levels in tap water: Taking haloacetic acids as a case study.

Chemosphere
Control of risks caused by disinfection by-products (DBPs) requires pre-knowledge of their levels in drinking water. In this study, a radial basis function (RBF) artificial neural network (ANN) was proposed to predict the concentrations of haloacetic...

Gas-phase trichloroethylene removal by Rhodococcus opacus using an airlift bioreactor and its modeling by artificial neural network.

Chemosphere
This study evaluated the biological removal of trichloroethylene (TCE) by Rhodococcus opacus using airlift bioreactor under continuous operation mode. The effect of inlet TCE concentration in the range 0.12-2.34 g m on TCE removal has studied for 55 ...

Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach.

Chemosphere
Polymer-assisted flocculation-dewatering of mineral processing tailings (MPT) is crucial for its environmental disposal. To reduce the number of laboratory experiments, this study proposes a novel and hybrid machine learning (ML) method for the predi...

Predicting the acute ecotoxicity of chemical substances by machine learning using graph theory.

Chemosphere
Accurate in silico predictions of chemical substance ecotoxicity has become an important issue in recent years. Most conventional methods, such as the Ecological Structure-Activity Relationship (ECOSAR) model, cluster chemical substances empirically ...

Modelling and Optimizing Pyrene Removal from the Soil by Phytoremediation using Response Surface Methodology, Artificial Neural Networks, and Genetic Algorithm.

Chemosphere
This study aimed to model and optimize pyrene removal from the soil contaminated by sorghum bicolor plant using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) with Genetic Algorithm (GA) approach. Here, the effects of indole a...