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A Machine Learning Approach for Predicting Defluorination of Per- and Polyfluoroalkyl Substances (PFAS) for Their Efficient Treatment and Removal

https://doi.org/10.1021/acs.estlett.9b00476

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inferred← citeshttps://doi.org/10.1038/s44221-025-00433-8openalex-snapshot

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inferred← citeshttps://doi.org/10.1039/c9cp06797copenalex-snapshot

Real-time degradation dynamics of hydrated per- and polyfluoroalkyl substances (PFASs) in the presence of excess electrons

inferred← citeshttps://doi.org/10.1039/d0cp02445gopenalex-snapshot

Examining the degradation of environmentally-daunting per- and poly-fluoroalkyl substances from a fundamental chemical perspective

inferred← citeshttps://doi.org/10.1039/d0cp02709jopenalex-snapshot

Machine-guided representation for accurate graph-based molecular machine learning

inferred← citeshttps://doi.org/10.1039/d0cp03694copenalex-snapshot

Harnessing deep neural networks to solve inverse problems in quantum dynamics: machine-learned predictions of time-dependent optimal control fields

inferred← citeshttps://doi.org/10.1039/d1cp05072aopenalex-snapshot

A machine learning approach for predicting the nucleophilicity of organic molecules

inferred← citeshttps://doi.org/10.1039/d2cp00439aopenalex-snapshot

Decoding hexanitrobenzene (HNB) and 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) as two distinctive energetic nitrobenzene compounds by machine learning

inferred← citeshttps://doi.org/10.1039/d2gc04341fopenalex-snapshot

Towards higher scientific validity and regulatory acceptance of predictive models for PFAS

inferred← citeshttps://doi.org/10.1039/d3dd00152kopenalex-snapshot

Spectroscopic constants from atomic properties: a machine learning approach

inferred← citeshttps://doi.org/10.1039/d3dd00169eopenalex-snapshot

Expansion of bond dissociation prediction with machine learning to medicinally and environmentally relevant chemical space

inferred← citeshttps://doi.org/10.1039/d3va00242jopenalex-snapshot

Modelling and predicting liquid chromatography retention time for PFAS with no-code machine learning

inferred← citeshttps://doi.org/10.1039/d5ew00888copenalex-snapshot

Biodegradation of per- and polyfluoroalkyl substances: mechanisms, challenges, and emerging strategies for sustainable remediation

inferred← citeshttps://doi.org/10.1039/d5nr03117fopenalex-snapshot

Mechanistic insights into plasmon-driven hot electron transfer from silver nanoclusters to PFAS: interplay of size and electronic structure

inferred← citeshttps://doi.org/10.1039/d5ra07508dopenalex-snapshot

Microbial and molecular approaches for PFAS transformation in soils: prospects and limitations

inferred← citeshttps://doi.org/10.1039/d5sc01624jopenalex-snapshot

A perspective of emerging trends in integrated PFAS detection and remediation technologies with data driven approaches

inferred← citeshttps://doi.org/10.1049/tje2.12184openalex-snapshot

Predicting liver disorder based on machine learning models

inferred← citeshttps://doi.org/10.1063/5.0246431openalex-snapshot

Amorphous-dominated MgO hollow spheres enhanced fluoride adsorption: Mechanism analysis and machine learning prediction

inferred← citeshttps://doi.org/10.1080/10643389.2023.2190313openalex-snapshot

Current applications and future impact of machine learning in emerging contaminants: A review

inferred← citeshttps://doi.org/10.1080/10643389.2025.2469868openalex-snapshot

New trend on chemical structure representation learning in toxicology: In reviews of machine learning model methodology

inferred← citeshttps://doi.org/10.1080/15376516.2024.2387733openalex-snapshot

Using machine learning to classify the immunosuppressive activity of per- and polyfluoroalkyl substances

inferred← citeshttps://doi.org/10.1080/15376516.2025.2570331openalex-snapshot

Computational evidence of cancer and reproductive toxicological potential from short-chain PFAS exposure through network toxicology and docking approaches

inferred← citeshttps://doi.org/10.1080/15422119.2023.2212295openalex-snapshot

Membrane Science Meets Machine Learning: Future and Potential Use in Assisting Membrane Material Design and Fabrication

inferred← citeshttps://doi.org/10.1088/1402-4896/adf14bopenalex-snapshot

Enabling ease of access to quantum chemistry with transformer-based text encoding and physics-informed multilayer perceptron

inferred← citeshttps://doi.org/10.1109/access.2021.3051505openalex-snapshot

Design and Analysis of An Data-Driven Intelligent Model for Persistent Organic Pollutants in the Internet of Things Environments

inferred← citeshttps://doi.org/10.1109/access.2026.3668252openalex-snapshot

Creep Prediction of Fluoroplastics Based on Physics Informed Neural Networks

inferred← citeshttps://doi.org/10.1109/eit57321.2023.10187291openalex-snapshot

Machine Learning Models for PFAS Tracking, Detection and Remediation: A Review

inferred← citeshttps://doi.org/10.1109/iceect61758.2024.10739142openalex-snapshot

Smart Commerce: Unleashing Machine Learning for Optimal Customer Experiences

inferred← citeshttps://doi.org/10.1109/urtc60662.2023.10534964openalex-snapshot

PFAS Incineration: Known Unknowns, Reaction Simulation, and ML to Predict Product Properties

inferred← citeshttps://doi.org/10.1155/2022/2239152openalex-snapshot

A Machine Learning Model to Predict Citation Counts of Scientific Papers in Otology Field

inferred← citeshttps://doi.org/10.1155/2022/4284146openalex-snapshot

PregTox: A Resource of Knowledge about Drug Fetal Toxicity

inferred← citeshttps://doi.org/10.1155/2022/7973446openalex-snapshot

Research on E-Commerce Database Marketing Based on Machine Learning Algorithm

inferred← citeshttps://doi.org/10.1155/2022/8211023openalex-snapshot

Modeling Energy Gap of Doped Tin (II) Sulfide Metal Semiconductor Nanocatalyst Using Genetic Algorithm‐Based Support Vector Regression

inferred← citeshttps://doi.org/10.1155/2022/8393498openalex-snapshot

DNA Methylation Biomarkers-Based Human Age Prediction Using Machine Learning

inferred← citeshttps://doi.org/10.1155/2022/8641194openalex-snapshot

Leukemia can be Effectively Early Predicted in Routine Physical Examination with the Assistance of Machine Learning Models

inferred← citeshttps://doi.org/10.1166/sam.2022.4302openalex-snapshot

Review on Perovskite-Type Compound Using Machine Learning

inferred← citeshttps://doi.org/10.12794/metadc1944346openalex-snapshot

Machine Learning in Computational Chemistry

inferred← citeshttps://doi.org/10.1371/journal.pone.0252753openalex-snapshot

Deep learning-based prediction of future growth potential of technologies

inferred← citeshttps://doi.org/10.1557/s43581-024-00122-1openalex-snapshot

Building a roadmap for safer and sustainable material chemistries: Addressing the PFAS problem through informatics and data-driven chemistry

inferred← citeshttps://doi.org/10.18596/jotcsa.1951243openalex-snapshot

Artificial Intelligence in Analytical Chemistry: A Critical Review of Applications, Model Performance, Validation, and Emerging Challenges

inferred← citeshttps://doi.org/10.20517/2394-4722.2025.18openalex-snapshot

A comprehensive study on the prognostic value of pyroptosis-associated genes in hepatocellular carcinoma

inferred← citeshttps://doi.org/10.20944/preprints202310.1855.v1openalex-snapshot

Leveraging Machine Learning for a Comprehensive Assessment of PFAS Nephrotoxicity

inferred← citeshttps://doi.org/10.20944/preprints202403.0627.v1openalex-snapshot

Application Of Machine Learning To Understand Pfas Occurrence, Distribution, Transport And Removal In Water

inferred← citeshttps://doi.org/10.21203/rs.3.rs-10285281/v1openalex-snapshot

Artificial-Intelligence-Guided Electrochemical Oxidation for Destroying Per- and Polyfluoroalkyl Substances (PFAS) in Drinking-Water Networks: A Transferable Framework from the United States to Peru

inferred← citeshttps://doi.org/10.2174/1389202923666220204153744openalex-snapshot

Comparisons of Forecasting for Survival Outcome for Head and Neck Squamous Cell Carcinoma by using Machine Learning Models based on Multi-omics

inferred← citeshttps://doi.org/10.2174/1389202923666220413114659openalex-snapshot

MetaConClust - Unsupervised Binning of Metagenomics Data using Consensus Clustering

inferred← citeshttps://doi.org/10.2174/1389202923666220511155939openalex-snapshot

Advancement in Deep Learning Methods for Diagnosis and Prognosis of Cervical Cancer

inferred← citeshttps://doi.org/10.2174/1389202923666220610121344openalex-snapshot

Establishment of New Genetic Markers and Methods for Sex Determination of Mouse and Human Cells using Polymerase Chain Reactions and Crude DNA Samples

inferred← citeshttps://doi.org/10.2174/1871527320666211213125847openalex-snapshot

Speech as a Biomarker for Depression

inferred← citeshttps://doi.org/10.2174/2210298102666220616114622openalex-snapshot

Multi-temporal Cloud Pixels Reconstruction Method for Optical Remote Sensing Satellite Images

inferred← citeshttps://doi.org/10.25046/aj090306openalex-snapshot

Leveraging Machine Learning for a Comprehensive Assessment of PFAS Nephrotoxicity

inferred← citeshttps://doi.org/10.26434/chemrxiv-2023-d147wopenalex-snapshot

Expansion of Bond Dissociation Prediction with Machine Learning to Medicinally and Environmentally Relevant Chemical Space

inferred← citeshttps://doi.org/10.26434/chemrxiv.12584930openalex-snapshot

A Database Framework for Rapid Screening of Structure-Function Relationships in PFAS Chemistry

inferred← citeshttps://doi.org/10.26434/chemrxiv.12584930.v1openalex-snapshot

A Database Framework for Rapid Screening of Structure-Function Relationships in PFAS Chemistry

inferred← citeshttps://doi.org/10.3390/ma15217782openalex-snapshot

Thermal Behavior Modeling Based on BP Neural Network in Keras Framework for Motorized Machine Tool Spindles

inferred← citeshttps://doi.org/10.3390/toxics11020098openalex-snapshot

A Machine Learning Model to Estimate Toxicokinetic Half-Lives of Per- and Polyfluoro-Alkyl Substances (PFAS) in Multiple Species

inferred← citeshttps://doi.org/10.47191/ijcsrr/v5-i10-08openalex-snapshot

PFAS Degradation Techniques – A Road towards Alleviating Organic Pollution

inferred← citeshttps://doi.org/10.54364/aaiml.2023.1182openalex-snapshot

A Novel Framework of Face Recognition using Heuristic Development of Ensemble Classifier Model

inferred← citeshttps://doi.org/10.69997/sct.135551openalex-snapshot

Streamlining Catalyst Development through Machine Learning: Insights from Heterogeneous Catalysis and Photocatalysis

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