Jahangiri Amir, Orekhov Vladislav
Department of Chemistry and Molecular Biology, Swedish NMR Centre, University of Gothenburg, Gothenburg, 40530, Sweden.
Commun Chem. 2024 Oct 27;7(1):244. doi: 10.1038/s42004-024-01325-w.
Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. In this study, we demonstrate that AI offers new opportunities beyond tasks addressed by traditional techniques. We developed and trained artificial neural networks to solve three problems that until now were deemed "impossible": quadrature detection using only Echo (or Anti-Echo) modulation from the traditional Echo/Anti-Echo scheme; accessing uncertainty of signal intensity at each point in a spectrum processed by any given method; and defining a reference-free score for quantitative access of NMR spectrum quality. Our findings highlight the potential of AI techniques to revolutionize NMR processing and analysis.
使用人工智能的智能信号处理方法在核磁共振（NMR）应用中越来越受到关注。在本研究中，我们证明了人工智能为传统技术所涉及的任务之外带来了新的机遇。我们开发并训练了人工神经网络来解决三个迄今为止被认为“不可能”的问题：仅使用传统回波/反回波方案中的回波（或反回波）调制进行正交检测；获取通过任何给定方法处理的频谱中每个点处信号强度的不确定性；以及定义一个无参考分数以定量评估NMR频谱质量。我们的研究结果突出了人工智能技术在彻底改变NMR处理和分析方面的潜力。
