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Beyond traditional magnetic resonance processing with artificial intelligence

Chemistry

Beyond traditional magnetic resonance processing with artificial intelligence

A. Jahangiri and V. Orekhov

This study by Amir Jahangiri and Vladislav Orekhov reveals how artificial intelligence can transform NMR spectroscopy by tackling previously unsolvable challenges. AI-driven neural networks have achieved breakthroughs in quadrature detection, quantifying signal intensity uncertainty, and creating a reference-free quality score for NMR spectra.

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Playback language: English
Abstract
This study demonstrates the potential of artificial intelligence (AI) in NMR spectroscopy, surpassing the capabilities of traditional methods. AI-powered neural networks were trained to solve three previously intractable problems: quadrature detection using only echo or anti-echo modulation; quantifying signal intensity uncertainty; and establishing a reference-free NMR spectrum quality score. The findings suggest AI can revolutionize NMR processing and analysis.
Publisher
Communications Chemistry
Published On
Oct 27, 2024
Authors
Amir Jahangiri, Vladislav Orekhov
Tags
artificial intelligence
NMR spectroscopy
neural networks
signal intensity
quadrature detection
spectral quality score

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