AIMC Topic: Fluorocarbons
Clear Filters Showing 1 to 10 of 43 articles
Prediction of Fraction Unbound in Human Plasma for Per- and Polyfluoroalkyl Substances: Evaluating Transfer Learning as an Algorithmic Solution to the Problem of Sparse Data.
Journal of chemical information and modeling
Jul 22, 2025
Fraction unbound in plasma () is a crucial parameter in physiologically based toxicokinetic (PBTK) models, representing the fraction of a chemical compound that is not sequestered by plasma proteins when present in the bloodstream. This is often used...
Occurrence, Sources, and Prioritization of Per- and Polyfluoroalkyl Substances (PFASs) in Drinking Water from Yangtze River Delta, China: Focusing on Emerging PFASs.
Molecules (Basel, Switzerland)
May 25, 2025
As regulations ban legacy PFASs, many emerging PFASs are being developed, leading to their release into the aquatic environment and drinking water. However, research studies on these emerging PFASs in drinking water are limited, and current standards...
PFHxA and PFHxS promote breast cancer progression in 3D culture: MEX3C-associated immune infiltration revealed by bioinformatics and machine learning.
Journal of hazardous materials
May 2, 2025
Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with widespread use and bioaccumulative potential. Short-chain PFAS such as perfluorohexanoic acid (PFHxA) and perfluorohexane sulfonate (PFHxS) have been introduced...
Unveiling PFAS hazard in European surface waters using an interpretable machine-learning model.
Environment international
Apr 30, 2025
Per- and polyfluoroalkyl substances (PFAS), commonly known as "forever chemicals", are ubiquitous in surface waters and potentially threaten human health and ecosystems. Despite extensive monitoring efforts, PFAS risk in European surface waters remai...
Assessing the association of multi-environmental chemical exposures on metabolic syndrome: A machine learning approach.
Environment international
Apr 17, 2025
Metabolic syndrome (MetS) is a major global public health concern due to its rising prevalence and association with increased risks of cardiovascular disease and type 2 diabetes. Emerging evidence suggests that environmental chemical exposures may pl...
Modeling PFAS Sorption in Soils Using Machine Learning.
Environmental science & technology
Apr 11, 2025
In this study, we introduce PFASorptionML, a novel machine learning (ML) tool developed to predict solid-liquid distribution coefficients () for per- and polyfluoroalkyl substances (PFAS) in soils. Leveraging a data set of 1,274 entries for PFAS in ...
Synergistic effect of horizontal transfer of antibiotic resistance genes between bacteria exposed to microplastics and per/polyfluoroalkyl substances: An explanation from theoretical methods.
Journal of hazardous materials
Apr 8, 2025
Microplastics (MPs) and per/polyfluoroalkyl substances (PFASs), as emerging pollutants widely present in aquatic environments, pose a significant threat to human health through the horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs)....
Machine learning for monitoring per- and polyfluoroalkyl substance (PFAS) in California's wastewater treatment plants: An assessment of occurrence and fate.
Journal of hazardous materials
Apr 1, 2025
Wastewater treatment plants (WWTPs) are significant sources of per- and polyfluoroalkyl substances (PFAS) pollution, but comprehensive monitoring and management are impractical and cost-prohibitive. To strengthen monitoring programs, we developed mac...
Molecular docking-QSAR-Kronecker-regularized least squares-based multiple machine learning for assessment and prediction of PFAS-protein binding interactions.
Journal of hazardous materials
Mar 29, 2025
Ubiquitous per- and poly-fluoroalkyl substances (PFAS) threaten human's health and attract worldwide attention. PFAS-mediated toxicity involves adverse effects of PFAS on proteins, and assessment of PFAS-protein binding interactions helps to explain ...
Explainable machine learning models enhance prediction of PFAS bioactivity using quantitative molecular surface analysis-derived representation.
Water research
Mar 13, 2025
The extensive use of per- and polyfluoroalkyl substances (PFAS) in industrial and consumer products poses health risks due to their toxicity. Computational toxicology approaches, particularly quantitative structure-activity relationship (QSAR) models...
Don't Miss the Future of Medicine
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 32006
- Neural Networks, Computer 30221
- Algorithms 27397
- Deep Learning 26901
- Artificial Intelligence 24835
- Robotics 13387
- Image Processing, Computer-Assisted 9735
- Retrospective Studies 9342
- Magnetic Resonance Imaging 6346
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4865
- Support Vector Machine 4769
- Computational Biology 4332
- Brain 4129
- Computer Simulation 3935
Recent Journals
- Scientific reports 6775
- Sensors (Basel, Switzerland) 4794
- PloS one 4200
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- 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 1378
- IEEE journal of biomedical and health informatics 1172
- Journal of chemical information and modeling 1064
- Nature communications 1044
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 873
- Journal of medical Internet research 861
- Briefings in bioinformatics 853