Guidance for good practice in the application of machine learning in development of toxicological quantitative structure-activity relationships (QSARs)

Recent years have seen a substantial growth in the adoption of machine learning approaches for the purposes of quantitative structure-activity relationship (QSAR) development. Such a trend has coincided with desire to see a shifting in the focus of methodology employed within chemical safety assessm...

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Detalles Bibliográficos
Autores principales: Belfield, Samuel J., Cronin, Mark T.D., Enoch, Steven J., Firman, James W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10171609/
https://www.ncbi.nlm.nih.gov/pubmed/37163504
http://dx.doi.org/10.1371/journal.pone.0282924

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10171609/
https://www.ncbi.nlm.nih.gov/pubmed/37163504
http://dx.doi.org/10.1371/journal.pone.0282924

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