2023
DOI: 10.1145/3542923
|View full text |Cite
|
Sign up to set email alerts
|

Rapid Convergence: The Outcomes of Making PPE During a Healthcare Crisis

Abstract: The U.S. National Institute of Health (NIH) 3D Print Exchange is a public, open-source repository for 3D printable medical device designs with contributions from clinicians, expert-amateur makers, and people from industry and academia. In response to the COVID-19 pandemic, the NIH formed a collection to foster submissions of low-cost, locally-manufacturable personal protective equipment (PPE). We evaluated the 623 submissions in this collection to understand: what makers contributed, how they were made, who ma… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
1
1

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 49 publications
0
1
0
Order By: Relevance
“…Makers could supply better labels by supplying well-documented source files for their meshes, but this requires a dramatic shift in the practices of these communities. More models are shared every day and new sub-domains of making are emerging with additional labels (e.g., clinical reviews on the NIH 3D print exchange [31]). Alternatively, the creation of datasets for 3D printing [11] and the release of novel approaches to 3D model generation [19] presents an opportunity to use latent representations of 3D models to generate meta-data for functionality.…”
Section: Opportunities For Richer Data Setsmentioning
confidence: 99%
“…Makers could supply better labels by supplying well-documented source files for their meshes, but this requires a dramatic shift in the practices of these communities. More models are shared every day and new sub-domains of making are emerging with additional labels (e.g., clinical reviews on the NIH 3D print exchange [31]). Alternatively, the creation of datasets for 3D printing [11] and the release of novel approaches to 3D model generation [19] presents an opportunity to use latent representations of 3D models to generate meta-data for functionality.…”
Section: Opportunities For Richer Data Setsmentioning
confidence: 99%