A Collaborative Study on the Classification of Silicone Oil Droplets and Protein Particles Using Flow Imaging Method.
Flow imaging
Machine learning
Protein particles
Silicone oil
Journal
Journal of pharmaceutical sciences
ISSN: 1520-6017
Titre abrégé: J Pharm Sci
Pays: United States
ID NLM: 2985195R
Informations de publication
Date de publication:
10 2022
10 2022
Historique:
received:
01
03
2022
revised:
07
07
2022
accepted:
07
07
2022
pubmed:
16
7
2022
medline:
21
9
2022
entrez:
15
7
2022
Statut:
ppublish
Résumé
In this study, we conducted a collaborative study on the classification between silicone oil droplets and protein particles detected using the flow imaging (FI) method toward proposing a standardized classifier/model. We compared four approaches, including a classification filter composed of particle characteristic parameters, principal component analysis, decision tree, and convolutional neural network in the performance of the developed classifier/model. Finally, the points to be considered were summarized for measurement using the FI method, and for establishing the classifier/model using machine learning to differentiate silicone oil droplets and protein particles.
Identifiants
pubmed: 35839866
pii: S0022-3549(22)00298-2
doi: 10.1016/j.xphs.2022.07.006
pii:
doi:
Substances chimiques
Proteins
0
Silicone Oils
0
Silicones
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2745-2757Informations de copyright
Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.