A Deep Learning Approach for Predicting FDA’s 510(k) Medical Device Recalls Using Device Citation Relationships.
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| Title: | A Deep Learning Approach for Predicting FDA’s 510(k) Medical Device Recalls Using Device Citation Relationships. |
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| Authors: | Zhu, Yi1 (AUTHOR) yzhu37@kent.edu, Sen, Soumya2 (AUTHOR) ssen@umn.edu, Everhart, Alexander3 (AUTHOR) everhart@wustl.edu, Karaca-Mandic, Pinar4 (AUTHOR) pkmandic@umn.edu |
| Source: | Information Systems Research (INFORMS). Dec2025, p1. 24p. |
| Database: | Business Source Ultimate |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: bsu DbLabel: Business Source Ultimate An: 190219826 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=190219826 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1287/isre.2024.1351 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 1 Titles: – TitleFull: A Deep Learning Approach for Predicting FDA’s 510(k) Medical Device Recalls Using Device Citation Relationships. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhu, Yi – PersonEntity: Name: NameFull: Sen, Soumya – PersonEntity: Name: NameFull: Everhart, Alexander – PersonEntity: Name: NameFull: Karaca-Mandic, Pinar IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 12 Text: Dec2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10477047 Titles: – TitleFull: Information Systems Research (INFORMS) Type: main |
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