Dimensionality reduction, and function approximation of poly (lactic-co-glycolic acid) micro-and nanoparticle dissolution rate
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86095763" target="_blank" >RIV/61989100:27240/15:86095763 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/15:86095763 RIV/61989100:27730/15:86095763
Result on the web
<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4327564/" target="_blank" >http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4327564/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.2147/IJN.S71847" target="_blank" >10.2147/IJN.S71847</a>
Alternative languages
Result language
angličtina
Original language name
Dimensionality reduction, and function approximation of poly (lactic-co-glycolic acid) micro-and nanoparticle dissolution rate
Original language description
Prediction of poly(lactic-co-glycolic acid) (PLGA) micro- and nanoparticles' dissolution rates plays a significant role in pharmaceutical and medical industries. The prediction of PLGA dissolution rate is crucial for drug manufacturing. Therefore, a model that predicts the PLGA dissolution rate could be beneficial. PLGA dissolution is influenced by numerous factors (features), and counting the known features leads to a dataset with 300 features. This large number of features and high redundancy within the dataset makes the prediction task very difficult and inaccurate. In this study, dimensionality reduction techniques were applied in order to simplify the task and eliminate irrelevant and redundant features. A heterogeneous pool of several regressionalgorithms were independently tested and evaluated. In addition, several ensemble methods were tested in order to improve the accuracy of prediction. The empirical results revealed that the proposed evolutionary weighted ensemble method o
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—
Result continuities
Project
—
Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Nanomedicine
ISSN
1178-2013
e-ISSN
—
Volume of the periodical
2015
Issue of the periodical within the volume
10
Country of publishing house
NZ - NEW ZEALAND
Number of pages
1129
Pages from-to
1119
UT code for WoS article
000348985600001
EID of the result in the Scopus database
2-s2.0-84922363645