Optimization of drug solubility inside the supercritical CO
Drug solubility
Extreme Gradient Boosting
LASSO
Polynomial regression
Supercritical CO2
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
01 Oct 2024
01 Oct 2024
Historique:
received:
29
08
2024
accepted:
26
09
2024
medline:
2
10
2024
pubmed:
2
10
2024
entrez:
1
10
2024
Statut:
epublish
Résumé
In this research paper, we explored the predictive capabilities of three different models of Polynomial Regression (PR), Extreme Gradient Boosting (XGB), and LASSO to estimate the density of supercritical carbon dioxide (SC-CO
Identifiants
pubmed: 39354064
doi: 10.1038/s41598-024-74553-8
pii: 10.1038/s41598-024-74553-8
doi:
Substances chimiques
Carbon Dioxide
142M471B3J
Niflumic Acid
4U5MP5IUD8
Solvents
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
22779Informations de copyright
© 2024. The Author(s).
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