Covering: up to March 2023Machine learning (ML) has emerged as a popular tool for
analyzing the structures of natural products (NPs). This review presents a summary of the …

This review explores the current applications of artificial intelligence (AI) in nuclear magnetic
resonance (NMR) spectroscopy, with a particular emphasis on small molecule chemistry …

The identification of molecular structure is essential for understanding chemical diversity and
for developing drug leads from small molecules. Nevertheless, the structure elucidation of …

Nuclear magnetic resonance (NMR) spectroscopy is highly unbiased and reproducible,
which provides us a powerful tool to analyze mixtures consisting of small molecules …

In the organic laboratory, the 13C nuclear magnetic resonance (NMR) spectrum of a newly
synthesized compound remains an essential step in elucidating its structure. For the …

Natural products (NPs), are small molecules produced naturally by any organism. As they
may be isolated in small quantities, having interesting biological activities and lush chemical …

This paper presents a proof-of-concept method for classifying chemical compounds directly
from NMR data without performing structure elucidation. This can help to reduce the time in …

The lack of machine‐readable data is a major obstacle in the application of nuclear
magnetic resonance (NMR) in artificial intelligence (AI). As a way to overcome this, a …

Inferring complete molecular structure from infrared (IR) spectra is a challenging task. In this
work, we propose SMEN (Spectra and Molecule Encoder Network), a framework for scoring …

The identification of a compound's chemical structure remains one of the most crucial
everyday tasks in chemistry. Among the vast range of existing analytical techniques NMR …