Name
Title | ||
|---|---|---|
Ensemble of Heterogeneous Flexible Neural Tree for the Approximation and Feature-Selection of Poly (Lactic-co-glycolic Acid) Micro- and Nanoparticle. |
Abstract | ||
|---|---|---|
In this work, we used an adaptive feature-selection and function approximation model, called, flexible neural tree (FNT) for predicting Poly (lactic-co-glycolic acid) (PLGA) micro-and nanoparticle's dissolution-rates that bears significant role in the pharmaceutical, medical, and drug manufacturing industries. Several factor influences PLGA nanoparticles dissolution-rate prediction. FNT model enable us to deal with feature-selection and prediction simultaneously. However, a single FNT model may or may not offer a generalized solution. Hence, to build a generalized model, we used an ensemble of FNTs. In this work, we have provided a comprehensive study for examining the most significant (influencing) features that influences dissolution rate prediction. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-29504-6_16 | PROCEEDINGS OF THE SECOND INTERNATIONAL AFRO-EUROPEAN CONFERENCE FOR INDUSTRIAL ADVANCEMENT (AECIA 2015) |
Keywords | DocType | Volume |
Poly (lactic-co-glycolic acid) (PLGA) micro- and nanoparticle,Flexible neural tree,Function approximation,Feature selection | Conference | 427 |
ISSN | Citations | PageRank |
2194-5357 | 1 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Varun Kumar Ojha | 1 | 32 | 9.25 |
| Ajith Abraham | 2 | 8954 | 729.23 |
| Václav Snasel | 3 | 1261 | 210.53 |