Modern machine-learning applications in ambient ionization mass spectrometry.
Mass Spectrom Rev
; 2024 Apr 26.
Article
en En
| MEDLINE
| ID: mdl-38671553
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.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Mass Spectrom Rev
Año:
2024
Tipo del documento:
Article
País de afiliación:
Rusia
Pais de publicación:
Estados Unidos