AI in analytical chemistry: Advancements, challenges, and future directions.

Analytical chemistry Artificial intelligence Chromatography Machine learning Spectroscopy

Journal

Talanta
ISSN: 1873-3573
Titre abrégé: Talanta
Pays: Netherlands
ID NLM: 2984816R

Informations de publication

Date de publication:
19 Mar 2024
Historique:
received: 28 12 2023
revised: 09 03 2024
accepted: 17 03 2024
medline: 4 4 2024
pubmed: 4 4 2024
entrez: 3 4 2024
Statut: aheadofprint

Résumé

This article explores the influence and applications of Artificial Intelligence (AI) in analytical chemistry, highlighting its potential to revolutionize the analysis of complex data sets and the development of innovative analytical methods. Additionally, it discusses the role of AI in interpreting large-scale data and optimizing experimental processes. AI has been fundamental in managing heterogeneous data and in advanced analysis of complex spectra in areas such as spectroscopy and chromatography. The article also examines the historical development of AI in chemistry, its current challenges, including the interpretation of AI models and the integration of large volumes of data. Finally, it forecasts future trends and the potential impact of AI on analytical chemistry, emphasizing the need for ethical and secure approaches in the use of AI.

Identifiants

pubmed: 38569367
pii: S0039-9140(24)00328-X
doi: 10.1016/j.talanta.2024.125949
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

125949

Informations de copyright

Copyright © 2024 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interestsRafael Cardoso Rial reports article publishing charges was provided by Federal Institute of Education Science and Technology of Mato Grosso do Sul. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Rafael Cardoso Rial (R)

Federal Institute of Mato Grosso do Sul, 79750-000, Nova Andradina, MS, Brazil. Electronic address: rafael.rial@ifms.edu.br.

Classifications MeSH