Artificial neural network-based pore size prediction of alginate gel scaffold for targeted drug delivery-Reference-Cited by-同舟云学术

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Artificial neural network-based pore size prediction of alginate gel scaffold for targeted drug delivery

Published:2022-10-28 Issue:6 Volume:35 Page:4683-4699
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Das Raja,Bhasarkar Jaykumar,Rastogi Amol,Saxena Raghav,Bal Dharmendra Kumar

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-022-07958-z.pdf

Reference37 articles.

1. Bal D, Ganguly S (2014) Enhancement of solute release from alginate scaffold with embedded sub-millimeter voids. J Biomater Sci Polym Ed 25(1):51–60

2. Rawal S, Patel M (2021) Bio-nanocarriers for lung cancer management: befriending the barriers. Nano-Micro Lett 13(1):1–54

3. Lee KY, Mooney DJ (2012) Alginate: properties and biomedical applications. Prog Polym Sci 37(1):106–126

4. Loh QL, Choong C (2013) Three-dimensional scaffolds for tissue engineering applications: role of porosity and pore size. 6:485-502

5. Youshia J, Lamprecht A (2016) Size-dependent nanoparticulate drug delivery in inflammatory bowel diseases. Expert Opin Drug Deliv 13(2):281–294

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial neural network prediction of particle size of agglomerated polybutadiene latex;Journal of Polymer Science;2024-03-15

2. GA-coupled ANN model for predicting porosity in alginate gel scaffolds;Journal of the Mechanical Behavior of Biomedical Materials;2023-12

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