AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Soil Pollutants

Showing 41 to 50 of 97 articles

Clear Filters

Efficient remediation of different concentrations of Cr-contaminated soils by nano zero-valent iron modified with carboxymethyl cellulose and biochar.

Journal of environmental sciences (China)
Nano zero-valent iron (nZVI) is widely used in soil remediation due to its high reactivity. However, the easy agglomeration, poor antioxidant ability and passivation layer of Fe-Cr coprecipitates of nZVI have limited its application scale in Cr-conta...

Predictive analysis and risk assessment of potentially toxic elements in Beijing gas station soils using machine learning and two-dimensional Monte Carlo simulations.

Journal of hazardous materials
Gas stations not only serve as sites for oil storage and refueling but also as locations where vehicles frequently brake, significantly enriching the surrounding soil with potentially toxic elements (PTEs). Herein, 117 topsoil samples from gas statio...

Prediction of PFAS bioaccumulation in different plant tissues with machine learning models based on molecular fingerprints.

The Science of the total environment
Due to the wastewater irrigation or biosolid application, per- and polyfluoroalkyl substances (PFASs) have been widely detected in agriculture soil and hence crops or vegetables. Consumption of contaminated crops and vegetables is considered as an im...

Quantifying the impact of factors on soil available arsenic using machine learning.

Environmental pollution (Barking, Essex : 1987)
Arsenic (As) can accumulate in edible plant parts and thus pose a serious threat to human health. Identifying the contributions of various factors to soil available As is crucial for evaluating environmental risks. However, research quantitatively as...

[Soil Cadmium Prediction and Health Risk Assessment of an Oasis on the Eastern Edge of the Tarim Basin Based on Feature Optimization and Machine Learning].

Huan jing ke xue= Huanjing kexue
Soil heavy metal pollution poses a serious threat to food security, human health, and soil ecosystems. Based on 644 soil samples collected from a typical oasis located at the eastern margin of the Tarim Basin, a series of models, namely, multiple lin...

Application of machine learning approaches to predict ammonium nitrogen transport in different soil types and evaluate the contribution of control factors.

Ecotoxicology and environmental safety
The loss of nitrogen in soil damages the environment. Clarifying the mechanism of ammonium nitrogen (NH-N) transport in soil and increasing the fixation of NH-N after N application are effective methods for improving N use efficiency. However, the ma...

Contribution assessment and accumulation prediction of heavy metals in wheat grain in a smelting-affected area using machine learning methods.

The Science of the total environment
Due to the diverse controlling factors and their uneven spatial distribution, especially atmospheric deposition from smelters, assessing and predicting the accumulation of heavy metals (HM) in crops across smelting-affected areas becomes challenging....

Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation.

Journal of hazardous materials
Urban fragmented vegetable fields offer fresh produce but pose a potential risk of heavy metal (HM) exposure. Thus, this study investigated HM sources and health risks in the soil-vegetable systems of Chongqing's central urban area. Results indicated...

Machine Learning Allowed Interpreting Toxicity of a Fe-Doped CuO NM Library Large Data Set─An Environmental In Vivo Case Study.

ACS applied materials & interfaces
The wide variation of nanomaterial (NM) characters (size, shape, and properties) and the related impacts on living organisms make it virtually impossible to assess their safety; the need for modeling has been urged for long. We here investigate the c...

Emerging investigator series: predicted losses of sulfur and selenium in european soils using machine learning: a call for prudent model interrogation and selection.

Environmental science. Processes & impacts
Reductions in sulfur (S) atmospheric deposition in recent decades have been attributed to S deficiencies in crops. Similarly, global soil selenium (Se) concentrations were predicted to drop, particularly in Europe, due to increases in leaching attrib...