AIMC Topic: Water Pollutants, Chemical
Clear Filters Showing 81 to 90 of 385 articles
Graphene FET biochip on PCB reinforced by machine learning for ultrasensitive parallel detection of multiple antibiotics in water.
Biosensors & bioelectronics
Nov 30, 2024
Antibiotics like Ciprofloxacin (Cfx), tetracycline (Tet) and Tobramycin (Tob) are commonly used against a broad-spectrum of bacterial infection. Recent surge in their uptake through the presence of their residues in environmental water has been linke...
Simulation and prediction of sulfamethazine migration, transformation and risk diffusion during cross-media infiltration from surface water to groundwater driven by dynamic water level: Machine learning coupled HYDRUS-GMS model.
Journal of environmental management
Nov 30, 2024
Seasonal water level fluctuations in rivers significantly influenced the cross-media migration, transformation, and risk diffusion of antibiotics from the vadose zone into groundwater. This study developed a coupled model integrating machine learning...
Design optimization of bimetal-modified biochar for enhanced phosphate removal performance in livestock wastewater using machine learning.
Bioresource technology
Nov 28, 2024
Mg-modified biochar shows high adsorption performance under weakly acidic and neutral water conditions. However, its phosphate removal efficiency markedly decreases in naturally alkaline wastewater, such as that released in livestock farming (anaerob...
Design and synthesis of a new recyclable nanohydrogel based on chitosan for Deltamethrin removal from aqueous solutions: Optimization and modeling by RSM-ANN.
International journal of biological macromolecules
Nov 27, 2024
In this study, a new magnetic biocompatible hydrogel was synthesized as an adsorbent for Deltamethrin pesticide removal. The optimal conditions and adsorption process of Deltamethrin by chitosan/polyacrylic acid/FeO nanocomposite hydrogel was studied...
Hybrid modeling techniques for predicting chemical oxygen demand in wastewater treatment: a stacking ensemble learning approach with neural networks.
Environmental monitoring and assessment
Nov 27, 2024
To ensure operational efficiency, promote sustainable wastewater treatment practices, and maintain compliance with environmental regulations, it is crucial to evaluate the parameters of treated effluent in wastewater treatment plants (WWTPs). Artific...
Cd adsorption prediction of Fe mono/composite modified biochar based on machine learning: Application for controllable preparation.
Environmental research
Nov 26, 2024
In this study, artificial neural network (ANN) and random forest (RF) were constructed to predict the Cd adsorption capacity of Fe-modified biochar. The RF model outperformed ANN model in accuracy and predictive performance (R = 0.98). Through the co...
Simulation, prediction and optimization for synthesis and heavy metals adsorption of schwertmannite by machine learning.
Environmental research
Nov 26, 2024
Due to its sea urchin-like structure, Schwertmannite is commonly applied for heavy metals (HMs) pollutant adsorption. The adsorption influence parameters of Schwertmannite are numerous, the traditional experimental enumeration is powerless. In recent...
Artificial intelligence-driven assessment of critical inputs for lead adsorption by agro-food wastes in wastewater treatment.
Chemosphere
Nov 25, 2024
Due to environmental concerns and economic value, the adsorption process using agricultural wastes is one of the promising methods to remove lead (Pb) from contaminated water. The relationships between agricultural waste properties, adsorption condit...
Prioritization of monitoring compounds from SNTS identified organic micropollutants in contaminated groundwater using a machine learning optimized ToxPi model.
Water research
Nov 20, 2024
Advanced suspect and non-target screening (SNTS) approach can identify a large number of potential hazardous micropollutants in groundwater, underscoring the need for pinpointing priority pollutants among detected chemicals. This present study theref...
Construction of interpretable ensemble learning models for predicting bioaccumulation parameters of organic chemicals in fish.
Journal of hazardous materials
Nov 20, 2024
Accurate prediction of bioaccumulation parameters is essential for assessing exposure, hazards, and risks of chemicals. However, the majority of prediction models on bioaccumulation parameters are individual models based on a single algorithm and lac...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823