Jung‐il Song

Materials Science

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 1 paper. Top paper: “Data-driven supervised machine learning to predict the compressive response of porous PVA/Gelatin hydrogels and in-vitro assessments: Employing design of experiments”.

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

International Journal of Biological Macromolecules(2023)10.1016/j.ijbiomac.2023.126906

N/A

0DataRank · unranked

20 citations

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