2020/01/13 by Dicheng Chen, Zi Wang, Chen, Dicheng +7 · 3 citations
Biochemistry, Genetics and Molecular Biology · Medicine · Physics and Astronomy · #Advanced MRI Techniques and Applications #Biological Physics (physics.bio-ph) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Physical sciences #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Medical Physics (physics.med-ph) #Metabolomics and Mass Spectrometry Studies #NMR spectroscopy and applications #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2001.04813
openalex publication_date 2020/01/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Since the concept of Deep Learning (DL) was formally proposed in 2006, it had a major impact on academic research and industry. Nowadays, DL provides an unprecedented way to analyze and process data with demonstrated great results in computer vision, medical imaging, natural language processing, etc. In this Minireview, we summarize applications of DL in Nuclear Magnetic Resonance (NMR) spectroscopy and outline a perspective for DL as entirely new approaches that are likely to transform NMR spectroscopy into a much more efficient and powerful technique in chemistry and life science.