Modelling and predicting liquid chromatography retention time for PFAS with no-code machine learning
Yunwu Fan, Yu Deng, Yi Yang, Xin Deng, Qianhui Li, Boqi Xu, Jianyu Pan, Sisi Liu, Yan Kong, Chang-Er Chen
Abstract
Machine learning is increasingly popular and promising in environmental science due to its potential in solving various environmental problems, particularly with simple code-free tools.
Topics & Concepts
Code (set theory)Simple (philosophy)Computer scienceRetention timeArtificial intelligenceMachine learningChromatographyChemistryProgramming languageEpistemologySet (abstract data type)PhilosophyAnalytical Chemistry and ChromatographyMetabolomics and Mass Spectrometry StudiesHealth, Environment, Cognitive Aging