Leveraging artificial intelligence to advance the understanding of chemical neurotoxicity.
Artificial intelligence
Commentary
Neurotoxicity
Journal
Neurotoxicology
ISSN: 1872-9711
Titre abrégé: Neurotoxicology
Pays: Netherlands
ID NLM: 7905589
Informations de publication
Date de publication:
03 2022
03 2022
Historique:
received:
06
12
2021
accepted:
25
12
2021
pubmed:
31
12
2021
medline:
8
4
2022
entrez:
30
12
2021
Statut:
ppublish
Résumé
Neurotoxicology is a specialty that aims to understand and explain the impact of chemicals, xenobiotics and physical conditions on nervous system function throughout the life span. Herein, we point to the need for integration of novel translational bioinformatics and chemo-informatics approaches, such as machine learning (ML) and artificial intelligence (AI) to the discipline. Specifically, we advance the notion that AI and ML will be helpful in identifying neurotoxic signatures, provide reliable data in predicting neurotoxicity in the context of genetic variability, and improve the understanding of neurotoxic outcomes associated with exposures to mixtures, to name a few.
Identifiants
pubmed: 34968636
pii: S0161-813X(21)00169-8
doi: 10.1016/j.neuro.2021.12.007
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
9-11Informations de copyright
Copyright © 2021 Elsevier B.V. All rights reserved.