Modern machine‐learning applications in ambient ionization mass spectrometry

IF 6.9 2区化学 Q1 SPECTROSCOPY

Mass Spectrometry Reviews Pub Date : 2024-04-27 DOI:10.1002/mas.21886

Anatoly A. Sorokin, Stanislav I. Pekov, Denis S. Zavorotnyuk, Mariya M. Shamraeva, Denis S. Bormotov, Igor A. Popov

引用次数: 0

Abstract

This article provides a comprehensive overview of the applications of methods of machine learning (ML) and artificial intelligence (AI) in ambient ionization mass spectrometry (AIMS). AIMS has emerged as a powerful analytical tool in recent years, allowing for rapid and sensitive analysis of various samples without the need for extensive sample preparation. The integration of ML/AI algorithms with AIMS has further expanded its capabilities, enabling enhanced data analysis. This review discusses ML/AI algorithms applicable to the AIMS data and highlights the key advancements and potential benefits of utilizing ML/AI in the field of mass spectrometry, with a focus on the AIMS community.

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环境电离质谱中的现代机器学习应用

本文全面概述了机器学习（ML）和人工智能（AI）方法在环境电离质谱（AIMS）中的应用。近年来，AIMS 已成为一种强大的分析工具，可对各种样品进行快速、灵敏的分析，而无需进行大量的样品制备。ML/AI 算法与 AIMS 的整合进一步扩展了其功能，使数据分析能力得到增强。本综述将讨论适用于 AIMS 数据的 ML/AI 算法，并重点介绍在质谱分析领域利用 ML/AI 的主要进展和潜在优势，重点关注 AIMS 社区。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mass Spectrometry Reviews 物理-光谱学

CiteScore

16.30

自引率

3.00%

发文量

期刊介绍： The aim of the journal Mass Spectrometry Reviews is to publish well-written reviews in selected topics in the various sub-fields of mass spectrometry as a means to summarize the research that has been performed in that area, to focus attention of other researchers, to critically review the published material, and to stimulate further research in that area. The scope of the published reviews include, but are not limited to topics, such as theoretical treatments, instrumental design, ionization methods, analyzers, detectors, application to the qualitative and quantitative analysis of various compounds or elements, basic ion chemistry and structure studies, ion energetic studies, and studies on biomolecules, polymers, etc.