Nuclear Magnetic Resonance and Artificial Intelligence
Stefan Kühn, Rômulo Pereira de Jesus, Ricardo M. Borges
Abstract
This review explores the current applications of artificial intelligence (AI) in nuclear magnetic resonance (NMR) spectroscopy, with a particular emphasis on small molecule chemistry. Applications of AI techniques, especially machine learning (ML) and deep learning (DL) in the areas of shift prediction, spectral simulations, spectral processing, structure elucidation, mixture analysis, and metabolomics, are demonstrated. The review also shows where progress is limited.
Topics & Concepts
Nuclear magnetic resonanceMagnetic resonance imagingComputer sciencePhysicsArtificial intelligenceMedicineRadiologyMetabolomics and Mass Spectrometry StudiesGeochemistry and Geologic MappingScientific Computing and Data Management