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

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

2023International Journal of Biological Macromolecules20 citationsDOI

Topics & Concepts

Self-healing hydrogelsGelatinMaterials scienceCompressive strengthPolyvinyl alcoholPorosityBiocompatibilityComposite materialBiomedical engineeringTissue engineeringPorosimetrySwellingChemical engineeringPorous mediumChemistryPolymer chemistryMetallurgyBiochemistryEngineeringMedicineElectrospun Nanofibers in Biomedical ApplicationsHydrogels: synthesis, properties, applications3D Printing in Biomedical Research
Data-driven supervised machine learning to predict the compressive response of porous PVA/Gelatin hydrogels and in-vitro assessments: Employing design of experiments | Litcius