Data-driven supervised machine learning to predict the compressive response of porous PVA/Gelatin hydrogels and in-vitro assessments: Employing design of experiments-Reference-Cited by-同舟云学术

Data-driven supervised machine learning to predict the compressive response of porous PVA/Gelatin hydrogels and in-vitro assessments: Employing design of experiments

Published:2023-12 Issue: Volume:253 Page:126906
ISSN:0141-8130
Container-title:International Journal of Biological Macromolecules
language:en
Short-container-title:International Journal of Biological Macromolecules

Author:

Khalvandi Ali,Tayebi Lobat,Kamarian Saeed,Saber-Samandari Saeed,Song Jung-il

Funder

Ministry of Education

National Research Foundation of Korea

National Institutes of Health

National Institute of Dental and Craniofacial Research

Publisher

Elsevier BV

Subject

Molecular Biology,General Medicine,Biochemistry,Structural Biology

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