Feature importance in multi-dimensional tissue-engineering datasets: Random forest assisted optimization of experimental variables for collagen scaffolds-Reference-Cited by-同舟云学术

Feature importance in multi-dimensional tissue-engineering datasets: Random forest assisted optimization of experimental variables for collagen scaffolds

Published:2021-12 Issue:4 Volume:8 Page:041403
ISSN:1931-9401
Container-title:Applied Physics Reviews
language:en
Short-container-title:Applied Physics Reviews

Author:

Nair Malavika¹^ORCID,Bica Ioana²³^ORCID,Best Serena M.¹^ORCID,Cameron Ruth E.¹^ORCID

Affiliation:

1. Cambridge Centre for Medical Materials, Department of Materials Science and Metallurgy, University of Cambridge, Cambridge, United Kingdom

2. Department of Engineering Science, University of Oxford, Oxford, United Kingdom

3. The Alan Turing Institute, London, United Kingdom

Funder

H2020 European Research Council

Engineering and Physical Sciences Research Council

Bill and Melinda Gates Foundation

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Link

https://aip.scitation.org/doi/pdf/10.1063/5.0059724

Reference63 articles.

1. Collagen for bone tissue regeneration

2. Collagen scaffolds for tissue engineering

3. Collagen engineering for biomaterial use

4. The synthesis and coupling of photoreactive collagen-based peptides to restore integrin reactivity to an inert substrate, chemically-crosslinked collagen

5. Tunable bioactivity and mechanics of collagen-based tissue engineering constructs: A comparison of EDC-NHS, genipin and TG2 crosslinkers

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