Nuclear Magnetic Resonance and Artificial Intelligence
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.
Authors
- Stefan Kühn (ORCID: https://orcid.org/0000-0002-5990-4157)
- Rômulo Pereira de Jesus (ORCID: https://orcid.org/0000-0003-1490-2112)
- Ricardo M. Borges (ORCID: https://orcid.org/0000-0002-7662-6734)
Institutions
- Universidade Federal do Rio de Janeiro (BR)
- University of Tartu (EE)
Publication Details
- Journal
- Encyclopedia
- Published
- 2024-10-18
- DOI
- https://doi.org/10.3390/encyclopedia4040102
- Citations
- 13
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 3.04
Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro